Movement disorder therapy and brain mapping system and methods of tuning remotely, intelligently and/or automatically

ABSTRACT

The present invention relates to methods for remotely and intelligently tuning movement disorder of therapy systems. The present invention still further provides methods of quantifying movement disorders for the treatment of patients who exhibit symptoms of such movement disorders including, but not limited to, Parkinson&#39;s disease and Parkinsonism, Dystonia, Chorea, and Huntington&#39;s disease, Ataxia, Tremor and Essential Tremor, Tourette syndrome, stroke, and the like. The present invention yet further relates to methods of remotely and intelligently or automatically tuning a therapy device using objective quantified movement disorder symptom data and/or brain activity mapped data to determine the therapy setting or parameters to be transmitted and provided to the subject via his or her therapy device. The present invention also provides treatment and tuning intelligently, automatically and remotely, allowing for home monitoring of subjects.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/992,270 which was filed on May 30, 2018 and which was acontinuation-in-part of U.S. patent application Ser. No. 15/280,045which was filed on Sep. 29, 2016 and issued as U.S. Pat. No. 10,092,754on Oct. 9, 2018, and which was a continuation of U.S. patent applicationSer. No. 14/963,687 which was filed on Dec. 9, 2015 and issued as U.S.Pat. No. 9,522,278 on Dec. 20, 2016, and which was a continuation ofU.S. patent application Ser. No. 14/022,376 which was filed on Sep. 10,2013 and issued as U.S. Pat. No. 9,238,142 on Jan. 19, 2016. U.S. patentapplication Ser. No. 14/022,376 further claims priority as each of: acontinuation-in-part of U.S. patent application Ser. No. 13/918,948,which was filed on Jun. 15, 2013 and issued as U.S. Pat. No. 9,211,417on Dec. 15, 2015; a continuation-in-part of U.S. patent application Ser.No. 14/022,323, which was filed on Sep. 10, 2013 and issued as U.S. Pat.No. 9,289,603 on Mar. 22, 2016; and a non-provisional applicationclaiming priority to provisional U.S. Patent Application Ser. No.61/698,890 which was filed on Sep. 10, 2012.

BACKGROUND OF THE INVENTION (1) Field of the Invention

The present invention relates to therapeutic medical apparatus systems,delivery systems, devices and/or methods, systems and methods formapping a subject's brain and correlating brain regions to particularsubject movements, and to apparatus and methods for using neuralstimulation to alleviate the symptoms of movement disorders, such asthose associated with Parkinson's disease, essential tremor, dystonia,and Tourette's syndrome, including tremor, bradykinesia, rigidity,gait/balance disturbances, and dyskinesia, and also for treating mentalhealth disorders such as major depression, bipolar disorder, andobsessive compulsive disorder for example. The present invention furtherrelates to the use of a movement disorder diagnostic device forautomatically and remotely adjusting, or tuning, therapeutic systems,devices, delivery systems, as well as methods thereof.

(2) Technology Review

A current trend in the treatment of diseases identified as beingassociated with the central nervous system is the stimulation of targetareas of the central nervous system to affect therapeutic benefit. Suchstimulation has been accomplished with, for example, implantedelectrodes that deliver electrical stimulation to target brain regions;one class of electrical neural stimulation devices has been categorizedunder the name “deep brain stimulation” (DBS). Although the exactneurological mechanisms by which DBS therapies succeed are complex andare not yet fully understood, such therapies have proven effective intreating Parkinson's disease motor symptoms (such as tremor,bradykinesia, rigidity, and gait disturbances), and investigation intothe use of DBS for the treatment of this and other neurological andmental health disorders, including major depression,obsessive-compulsive disorder, tinnitus, obesity, criminal tendencies,and antisocial disorders, is ongoing.

Access to movement disorder specialists to assist in diagnosis andtreatment of such disorders may require many clinical visits and can befinancially burdensome for the geographically disparate subset of the PDpopulation or those unable to travel. Movement disorder center locationscan limit access to well-trained clinicians and effective symptommanagement. Rural patients in one study had a significantly worsequality of life score than their urban counterparts. Telehealthtechnologies such as home monitoring and online patient data managementcan have a significant impact on the equity, accessibility, andmanagement of PD for patients who live in rural and remote communitiesor those unable to travel.

With DBS therapy, electrical pulses characterized by amplitude (volts),current (amps), frequency (Hz), and pulse width (microseconds) areregulated by an implantable pulse generator (IPG) placed beneath theskin. Stimulation affects motor symptoms on the contralateral side,i.e., right side tremor will be treated on the left brain. Althoughmedication is not eliminated, it is typically reduced significantly. DBSefficacy decreases over time as the body adjusts to stimulation andprotein buildup around electrode lead attenuates electrical field.Programming sessions are required throughout the patient's lifetime,though the frequency of adjustments is typically greater at first. TheIPG typically includes a battery and circuitry for telemeteredcommunication with an external programming device used to adjust, or“tune,” DBS stimulation parameters, which may include, but are notlimited to, stimulation frequency, amplitude, pulse width (orwavelength), waveform type, and contact configuration (that is, theselection of which electrodes are utilized from among the electrodesavailable on a lead, and, if two or more electrodes are active, therelative polarity of each), and the like. These parameters are initiallyset during implantation surgery separately and independently for eachDBS lead that is implanted, and are then further fined-tuned in theoutpatient clinic or in a doctor's office following surgery to maximizetherapeutic benefit and minimize undesirable stimulation-induced sideeffects.

DBS programming may be performed by movement disorder neurologists,neurosurgeons, fellows, occupational and physical therapists, nurses, oremployees of the DBS manufacturer. However, many patients haveinadequate access to DBS programming due to physicians and patientsrelocating as well as implantations occurring at facilities far from apatient's home. Additionally, there is a shortage of health careprofessionals highly trained in DBS programming.

The approaches to programming can vary greatly across institutions.Strict iterative procedures whereby initial subjective test resultsbased on human observation are used to determine the effect theparameters have of the patient and new parameters are determined basedon those results by clinician calculation and observation are quite timeconsuming and therefore rarely followed. Many programmers make educatedguesses as to the best settings based on their prior experience;however, this experience can vary across institutions and may not takeinto account varied lead positioning. Many programmers simply ignorebipolar or tripolar configurations whereby stimulation is provided fromtwo or three contacts on a single DBS lead simultaneously, and do notadjust frequency or pulse width in an attempt to speed the programmingprocess; however, neglecting these options can lead to suboptimalpatient outcomes. In constant-voltage IPGs, the voltage of each pulse isset, but the current will automatically change based on the electrodeimpedance. This leads to variable amounts of current being delivered thestimulation target as impedances change. Additionally, since impedanceswill vary across electrode contacts, applying the same voltage on twodifferent contacts will likely lead to different therapeutic currentsbeing delivered. On the other hand, constant-current IPGs specify thecurrent to be delivered and adjust the voltage accordingly based on theimpedance. Since the therapeutic effects of DB S are based on currentdelivered at a given target, constant-current IPGs are preferable toconstant-voltage IPGs.

While the above-described equipment and procedures are typical as of thefiling of this application, variations and refinements may becomecommonplace as neural implant technology advances. Conceivably, uses ofa multiplicity of DBS leads or networks of DBS leads may provide greatercoverage, enabling the stimulation of larger and more varied targetareas, and miniaturization and improved telemetry may obviate the needfor the extension cable and/or the IPG altogether as leads becomeself-powering and/or self-controlling or permit for built-in telemetry.Advances in nanotechnology and materials may also allow DBS leads in thefuture to become self-repositioning, self-cleaning, or resistant tobiological rejection for improved long-term therapeutic operation andmore precisely targeted implantation.

The current standard in evaluating the severity of movement disordersymptoms in Parkinson's disease is the manually human scored UnifiedParkinson's Disease Rating Scale (UPDRS) used to score motor tests, manyof which involve repetitive movement tasks such as touching the nose anddrawing the hand away repeatedly, or rapidly tapping the fingerstogether. A battery of exercises, typically a subset of the upperextremity motor section of the UPDRS, is normally completed during DBSlead placement surgery and subsequent programming sessions to evaluateperformance while a clinician qualitatively assesses symptoms. Each testis typically evaluated by a clinician based solely on visual observationand graded on a scale that typically ranges from 0 (minor) to 4(severe).

Postoperatively, assessing DBS response and reprogramming stimulationparameters require a significant time commitment. Several stimulationparameters can be modified, including, but not limited to, electrodepolarity, amplitude, current, pulse width, waveform type, and frequency.DBS programming and patient assessment may be performed by a variety ofhealthcare professionals, including movement disorder neurologists,neurosurgeons, fellows, occupational and physical therapists, nurses,and employees of the DBS manufacturer. Stimulation optimization istypically performed based on results of an exam such as the UPDRS, withthe patient in four states (off medication/off DBS, off medication/onDBS, on medication/off DBS, and on medication/on DBS). The process ofDBS adjustment is iterative and largely involves trial-and-error.Programming and patient assessment from preoperatively to one year aftersurgery requires approximately 30 hours of nursing time per patient.

Clinicians presently lack tools that combine physiological, electrical,and behavioral data to optimize electrode placement and stimulatorprogramming. Optimizing electrode placement and stimulation parametersimproves patient outcome by alleviating motor symptoms and minimizingcomplications. The present invention addresses this need for improvedelectrode placement and adjustment of deep brain stimulation parametersby providing a repeatable, automated or semi-automated tool that canassist stimulation parameter tuning during surgical electrode placementand outpatient programming sessions. In particular, the presentinvention aims to provide methods for the collection and transmission ofobjective biokinetic data, which data is then processed to outputobjective movement disorder symptom severity measures on a continuousscale in real-time to guide clinician decision making. The improvedresolution and repeatable results of the present invention should reducetime and costs of DBS procedures as well as improve patient outcomes.

Subject movement of virtually all types: voluntary, involuntary, normal,symptomatic, etc., typically and generally originates with a signal fromthe subject's brain or spinal cord. All movements, from basic movements,such as walking or waving one's hand, to complex movements, such asplaying a sport or a musical instrument, require coordination andcommunication between the subject's brain and the rest of the subject'sbody, in real time, where the brain initiates and controls the movementsof the body to perform the particular movement—either consciously orsubconsciously. Typically, body movement is controlled largely by themotor cortex region of the brain, but the motor cortex is notnecessarily employed for all movements in all subjects, or in allsituations. Basic movements may still be performed, if, for example, themotor cortex is damaged or injured. However, complex voluntary movementsalmost always require sophisticated and complex operation of the motorcortex to direct the body's movements. Essentially, the type of movementbeing performed activates and requires excitation of different portionsof the brain, even different portions of the motor cortex itself, andfurther even different combinations of individual neurons within themotor cortex or other parts of the brain. Thus, movement is notcontrolled or governed based on the operation of each individual neuron,but rather the complex interactions of individual neurons in relation toeach other in order to perform different combinations of movements.Further complicating the correlation of the brain's control overmovement is the introduction of injury or disease states, for examplemovement disorders, which lead to abnormal or changed interactions ofneurons and symptomatic movements. Symptomatic movement may be caused byany number of sources, including, but not limited to faulty brainfunction, interrupted signal transmission, damaged receptors, and thelike. The complex interactions between neurons do not end in the brain,but rather continue throughout the neurons in the subject's entire body.In order to move one's foot, particular neurons are employed in thesubject's brain, and the signal to move the foot must be transmittedthrough neurons all the way to the subject's foot in order to cause thefoot to move. Thus, even the most simple of movements is the result ofsuch a chain of interactions between neurons, which makes the process ofmapping brain activity related to movement even more difficult toascertain. Although the nervous system typically has numerousredundancies or alternative routes built into the neurological pathways,it may require as few as one neuron misfiring anywhere in the chain, forany reason, to generate symptomatic movement in any part of thesubject's body. Further, each individual subject's nervous systemanatomy is unique, so the same symptom in two different subjects, mayoriginate from an entirely different source in each of the subjects.Brain mapping, the study of the anatomy and function of the brain andspinal cord, allows for the correlation of an individual subject's brainfunction with corresponding results distal from the brain—such asmovement. In other words, brain mapping allows for identification of theportion, region, or structure of the subject's brain that corresponds toa particular movement or symptom. It follows, then, that such mappingand correlation would allow for more accurately targeted therapeuticstimulation. Brain mapping can generally be performed by any number ofmethods including imaging (both non-invasive and invasive techniques areused), immunohistochemistry, molecular and optogenetics, engineering,neurophysiology and nanotechnology means, with imaging, or morespecifically neuroimaging, being the most common and most efficacious.Numerous neuroimaging methodologies are known and have been used totrack brain activity and help to map it, including, but not limited to,cortical stimulation mapping, diffusion magnetic resonance imaging(dMRI), electroencephalogram (EEG), electrocorticography, functionalmagnetic resonance imaging (fMRI), medical image computing, and positronemission tomography (PET). Neuroimaging methods of brain mapping areused to obtain brain imaged that are supplemented and augmented byresults of additional data (such as other imaging results or non-imagingdata) that serve to project various behavior, or measures of behavioronto the brain regions or structures from with the initiate. An exampleof such a brain map result is called a connectogram, and depictscortical regions of the subject's brain around a circle where thecortical regions are organized according to the lobe of the brain wherethe region is located, and where concentric circles within the ring arerepresentative of common neurological measurements (e.g., corticalthickness or curvature), and weighted lines are used to connect thevarious concentric circles indicating connections between the variouscortical regions, the weight being indicative of the strength of theconnection. Using such a map, a subject's movement can be correlated tothe several portions of the brain that contribute to that movement, andthe strength of the correlation may be shown. However, many brainmapping techniques known in the art exhibit a very low resolution,sometimes including hundreds of thousands of neurons in a single voxelof the image. This is clearly due in large part to the complex andcomplicated nature of the nervous system. It is also due in part to thefact that each individual function of the subject (not just movement)involves input or excitation of several parts of the brain. That is tosay, liftings one's arm may not be solely attributable to an individualor small group of neurons located on the motor cortex for all or evenmany individuals. Examples of such traditional brain mapping systems andtechniques are known in the art, for example in U.S. Pat. No. 7,706,871to Devlin et al., U.S. Pat. No. 4,421,122 to Duffy, U.S. Pat. No.4,862,359 to Trivedi et al., U.S. Pat. No. 4,649,482 to Raviv et al.,and 4,844,086 to Duffy, as well as U.S. Patent Publication Serial no.2002/0099295 to Gil et al., all of whose disclosures are hereinincorporated by reference. Converse to the systems and methods known inthe art, however, highly accurate brain mapping often requireshigh-resolution work focused on individual brain circuits, or at least,small groups of such circuits. In other words, brain mapping is a highlysensitive and computationally intense procedure, that is not easily andreadily performed in an accurate manner alone, and even less so whileadding additional variables such as sensor input and stimulation fromdevices such as therapeutic devices (e.g., functional electricalstimulation (FES), DBS, and the like).

It is therefore an object of the present invention to provide a systemfor screening patients for viability of DBS therapy prior to extensive,repetitive travel and expense, and prior to requiring surgicalimplantation of DB S leads. It is further an object of the presentinventions to provide such a screening system to help minimizehealthcare costs and to prevent adverse effects in patient quality oflife associated with ineffective or unnecessary surgery, and to helpclinicians to better select courses of treatment for patients. It isfurther an object of the present invention to couple at-home patientviability screening and automatically-assigned quantitative motorassessments with procedures and practices for DBS implantation andparameter tuning and programming in semi-automatic and automatic ways toprovide improved and less costly movement disorder patient therapy,including but not limited to remote, semi-automatic and automatictitration and control of therapeutic actuators and treatment devices. Itis still further an object of the present invention to provide brainmapping capability that is functionally accurate and subject-specific,particularly related to the subject's movement and symptoms of movementdisorders. It is yet still a further object of the present invention touse the brain mapping functionality to increase the accuracy andminimize the stimulation required in order to tune the subject's therapydevice.

It is further an object of the present invention to provide automatedfunctional mapping based on objective motor assessments and algorithmsfor resolving an optimal set of programming parameters out of thethousands of possibilities to provide an expert system to enableprogramming at a local medical facility. The system is designed for useby any healthcare professional, but is particularly aimed at allowing ageneral practitioner or nurse with minimal training or experience in DBSprogramming and disease management to increase access to high-qualitypostoperative DBS management. The system will minimize the requiredexpertise of the clinician by requiring little or no advanced knowledgeof complex neurophysiology or Mill imaging.

Existing systems for quantifying Parkinson's disease motor symptoms aredescribed in this application's parent applications (Provisional U.S.Patent Application Ser. No. 61/698,890, U.S. Pat. Nos. 9,211,417,9,289,603), which are herein incorporated by reference, and whichdescribe novel systems for measuring motor dysfunction symptoms andcomputing measures based on UPDRS scores therefrom. Additionally, thepresent invention and system may benefit from similar and relatedsystems, methods and devices such as those described in U.S. patentapplication Ser. No. 13/152,963, U.S. patent application Ser. No.13/185,287, U.S. Pat. No. 8,702,629, U.S. patent application Ser. No.11/432,583, U.S. patent application Ser. No. 12/250,792, U.S. Pat. Nos.8,679,038, 8,845,557, and U.S. patent application Ser. No. 13/785,273,which are hereby incorporated by reference. Preferably, the system andmethods described therein are incorporated, in whole or in part, intothe present invention as a means of automatic symptom quantification.The resultant scores objectively quantify movement disorder symptomsadvantageously using a scale that is familiar to clinicians.

SUMMARY OF THE INVENTION

The present invention relates to methods for semi-automatically andautomatically adjusting, or tuning, treatment parameters in movementdisorder therapy devices and systems, and more specifically foroptionally remotely and intelligently adjusting or tuning such devicesand systems. Semi-automatic adjustment includes providing the clinician,physician or technician with objective, quantitative orsemi-quantitative data or measurements related to a subject's movementdisorder symptoms, determining desired parameters, and then remotelyentering those parameters either semi-automatically or automaticallyinto the subject's therapy device. Semi-automatic or automaticadjustment (including but not limited to remote adjustment byclinicians) includes for example providing data including, but notlimited to, objective, quantitative or semi-quantitative data and/ormeasurements related to a subject's movement disorder symptoms to analgorithm, using the data or measurements for determining desiredparameters using the algorithm, and then entering those parameterseither semi-automatically (i.e., allowing clinician, physician ortechnician to review and/or approve/adjust) or to automatically into thesubject's therapy device. Alternatively or in addition, semi-automaticor automatic adjustment may not require sensors to provide data and/ormeasurements related to a subject's movement disorder symptoms, butrather may use qualitative or quantitative information such as, forexample, traditional telemedicine techniques or remote observation by aclinician, physician or technician via video connection. In suchembodiments, the clinician, physician or technician would perform a moreclassic scoring of the subject's symptoms rather than using quantifieddata and/or measurements from sensors attached to the subject's body ordevice such as for example by using video links between the clinicianand the patient or subject.

Remote adjustment or tuning includes the control and or decisionregarding the therapy parameters to be programmed into the subject'stherapy device being located remotely from the subject. For example,remote adjustment or tuning may be controlled by a clinician, physicianor technician or an automated or semi-automated system using datatransmitted from the subject and/or his or her therapy device withoutthe subject having to travel to the clinical site to for such data to beobtained or transferred. The present invention further relates to asystem for screening patients to determine if they are viable candidatesfor certain therapy modalities. The present invention still furtherprovides methods of quantifying movement disorders for the treatment ofpatients who exhibit symptoms of such movement disorders including, butnot limited to, Parkinson's disease and parkinsonism, Dystonia, Chorea,and Huntington's disease, Ataxia, Tremor and Essential Tremor, Tourettesyndrome, and the like. The present invention yet further relates tomethods of automatically and intelligently tuning a therapy device usingobjective quantified movement disorder symptom data acquired by amovement disorder diagnostic device with the therapy settings orparameters to be provided to the subject via his or her therapy device.

Objective measurement and quantification of a subject's movementdisorder symptoms, which is a preferable embodiment of the presentinvention includes symptoms such as tremor, bradykinesia, dyskinesia,gait and/or balance disturbances, and the like requires, as a firststep, a measurement of the movement. This measurement can be performedby measuring a single movement metric, different movement metrics, or acombination of a number of movement metrics; and the movement metric ormetrics being measured may include linear or rotational displacement,velocity, or acceleration, or any other metric that could give aquantitative indication of motion; and the part of the body beingmeasured for motion may be a limb (as at a wrist, ankle, or finger) ormay be the trunk of the body (as at a shoulder or torso), and the head.Sensors used for measuring body movement or motion include gyroscopesand accelerometers, preferably miniaturized, electromagnets, video, amultitude of sensors or system disclosed herein, or other sensors knownto those skilled in the art. Additionally, sensors for measuringphysiological signals such as electromyogram (EMG), electrooculogram(EOG), electroencephalogram (EEG), electrocardiogram (EKG),electrocorticogram (ECoG), or other physiological signals which candirectly or indirectly measure movement metrics in the subject may beincluded if such sensors and signals may be used to sense, detect,measure, and/or quantify the subject's external body motion, or relatedaspects. Other systems that can be used to detect and measure bodymotion include motion capture systems, machine vision systems, sonic orlaser Doppler velocity transducers, infrared systems, GPS, or any othersystem known to those skilled in the art. The movement disorderdiagnostic device used in the present invention may incorporate one ormore of any of the above sensors or systems. Currently used movementdata acquisition and diagnostic systems, such as described in U.S. Pat.No. 8,187,209, herein incorporated by reference, may similarly be usedin certain embodiments of the present invention. In the presentdisclosure, “movement data” is construed as including, but not beinglimited to, any signal or set of signals, analog or digital,corresponding to movement of any part of the body or multiple parts ofthe body, independently or in conjunction with each other. This includesphysiological signals from which movement data or symptoms can bederived. Preferably, this movement data is generated with a movementsensor such as for example a gyroscope and/or an accelerometer, andadditionally or optionally a video sensor.

Movement may be continuously measured over long time spans, or may bemeasured only over a short time span, for example, as during the periodof one or more tests taken from or based on the UPDRS motor exam. Ameasurement time period comprises two separate time periods: (i) asensing time during which the movement disorder diagnostic device andits included sensors are used to sense and measure the subject'sexternal physical motion; and (ii) a processing or calculation timewherein the measured motion data is used to calculate objective scoresand/or other kinematic data that quantify the severity of the subject'smovement disorder symptoms and side effects, and wherein the scores. Themeasurement time required to adequately and accurately sense, measureand quantify the subject's movement can depend on the particularmovement test or task being performed, which typically corresponds to aparticular symptom of a movement disorder. Generally, however, thesystem aims to minimize the amount of measurement time required toobtain sufficient movement data and provide quantitative scores and/orkinematic data to continue the evaluative process. Preferably, themeasurement time required to provide objective scores and/or kinematicdata is less than about 120 minutes. More preferably, the measurementtime required to provide objective scores and/or kinematic data is lessthan about 90 minutes. Still more preferably, the measurement timerequired to provide objective scores and/or kinematic data is less thanabout 60 minutes. Yet more preferably, the measurement time required toprovide objective scores and/or kinematic data is less than about 45minutes. Even more preferably, the measurement time required to provideobjective scores and/or kinematic data is less than about 30 minutes.Still yet more preferably, the measurement time required to provideobjective scores and/or kinematic data is less than about 15 minutes.Still even more preferably, the measurement time required to provideobjective scores and/or kinematic data is less than about 10 minutes.Yet still more preferably, the measurement time required to provideobjective scores and/or kinematic data is less than about 5 minutes. Yeteven more preferably, the measurement time required to provide objectivescores and/or kinematic data is less than about 60 seconds. Even stillmore preferably, the measurement time required to provide objectivescores and/or kinematic data is less than about 30 seconds. Even yetmore preferably, the measurement time required to provide objectivescores and/or kinematic data is less than about 15 seconds. Still evenyet more preferably, the measurement time required to provide objectivescores and/or kinematic data is less than about 1 second.

Many embodiment utilize separate and discrete time periods for measuringmovement, brain activity, or both in several iterations. Typically, suchdiscrete time periods (example a first, second, third, etc.) are usedfor obtaining measurements to train an algorithm for ongoing and futureuse of the devices, systems, and methods of the present invention. Forexample, in some embodiments measurements are taken during a first timeperiod, treatment or therapy may be adjusted, and measurements may betaken during a second time period. Effectively, such second time periodmeasurements can be use to determine the effect of the adjustments tothe treatment or therapy parameters. Such adjustment preferably leads toa decrease in symptoms or side effects. In any event, such measurementduring iterative time periods may be performed to obtain a set of datawhich correlates treatment or therapy parameters to resultantmeasurements, and thus the algorithm(s) may be trained in order toassociate certain parameters with certain outcomes. Thus, over time, thealgorithm may be trained to require fewer types of measurements in orderto provide the best treatment or therapy to address the subject'ssymptoms or side effects. As a specific, though non-limiting, example,during the iterative measurement time periods, the system may measureboth movement (including symptoms and/or side effects of treatment ortherapy) and brain activity of the subject. The iterative trainingprocess allows the algorithm to be trained in the correlation betweensuch movement and brain activity. In time, movement may no long need tobe measured during every measurement time period, or at all, and thesystem may operate only on measured brain activity by which the trainedalgorithm would recognize the symptoms or side effects based on suchmeasured brain activity, but would not require measured movement, andcan then generate treatment or therapy parameters to address thosesymptoms or side effects.

In some embodiments, a periodic system may be employed wherein thesubject's external body motions are sensed, measured, and quantifiedrepeatedly but at predefined or altering intervals. In such periodicembodiments, the periodic measurements preferably conform to the abovedescribed measurement time period standards. Embodiments utilizingperiodic measurement may begin when the subject attaches or dons themovement disorder diagnostic device, and may involve a step ofinstructing the subject to attach or don the device to begin ameasurement period. Protocols for periodic measurement may be envisionedwherein a subject follows a particular schedule for measurement andquantification of movement disorder data, and wherein the schedule maychange throughout the course of treatment and/or therapy. In still otherembodiments, a continuous monitoring system may be employed wherein themovement disorder diagnostic device continuously senses, measures andquantifies the subject's external body movements over extended periodsof time, such as hours, days, weeks or months. Preferably, in thecontinuous measurement embodiments, the diagnostic device senses,measures and/or quantifies the subject's external body movementssubstantially continuously, with no breaks or stoppages in itsoperation. However, the limits of continuous operation may be defined bycharacteristics of the device, such as battery life, form factor andconstruction (e.g., if it needs to be removed to shower), and other suchconcerns.

The movement disorder diagnostic device contains at least one electroniccomponent that further may contain internal or onboard memory forstorage of the movement data such that the data may be transferred at alater time. More preferably, the movement disorder diagnostic devicefurther may contain communications electronics, which transmit themovement data to an external device for storage and/or analysis. Thecommunication electronics preferably is/are wireless, and mostpreferably is/are radio frequency wireless. The external device may be acentralized storage database, parallel databases, a cloud-baseddatabase, a computer, tablet, cell phone including for examplesmartphone, personal data assistant (PDA) or similar device, or acombination of database and computer or communication devices.Preferably, such transmission of data occurs substantially in real-time.By real-time, it is meant that preferably, data is transmitted within 30minutes of being acquired, measured, or calculated. More preferably,data is transmitted within 20 minutes of being acquired, measured, orcalculated. Still more preferably, data is transmitted within 10 minutesof being acquired, measured, or calculated. Yet more preferably, data istransmitted within 5 minutes of being acquired, measured, or calculated.Even more preferably, data is transmitted within 5 minutes of beingacquired, measured, or calculated. Still yet more preferably, data istransmitted within 3 minutes of being acquired, measured, or calculated.Even yet more preferably, data is transmitted within 60 seconds of beingacquired, measured, or calculated. Yet still more preferably, data istransmitted within 45 seconds of being acquired, measured, orcalculated. Yet even more preferably, data is transmitted within 30seconds of being acquired, measured, or calculated. Even still morepreferably, data is transmitted within 15 seconds of being acquired,measured, or calculated. Even yet more preferably, data is transmittedwithin 5 seconds of being acquired, measured, or calculated. Still evenyet more preferably, data is transmitted within 1 second of beingacquired, measured, or calculated. Yet even still more preferably, datais transmitted substantially simultaneously within milliseconds of beingacquired, measured, or calculated.

Following measurement of symptomatic movement, the next step inobjective quantification of a subject's movement disorder symptoms isthe extraction of statistical kinematic features from the acquiredmovement data via processing. This processing may take place during orfollowing data acquisition and may occur within a movement dataacquisition device or within a different processing device, such as apersonal computer, PDA, smart phone, tablet computer, touch screeninterface, or the like, with which the acquisition device interfaces,either through a cable connection or by wireless transmission. Usefulkinematic features that may be extracted from gyroscopic data mayinclude, for example, peak power angular velocity, peak power angle, RMSangular velocity, frequency, maximum amplitude, maximum peak-to-peakamplitude, mean angular velocity, and wavelet parameters, as well as thecovariance or standard deviation over time of any of these metrics.Useful kinematic features that may be extracted from accelerometer datamay include, for example, peak power acceleration, peak power velocity,peak power position, RMS acceleration, RMS velocity, RMS position,frequency, maximum amplitude, maximum peak-to-peak amplitude, meanacceleration, and wavelet parameters, as well as the covariance orstandard deviation over time of any of these metrics. In a movement dataacquisition system, or movement disorder diagnostic measuring apparatus,that combines a three-axis accelerometer and a three-axis gyroscope toproduce 6 channels of movement data, one or any combination of the abovekinematic features can be extracted from any of the 6 kinematic channelsto be used as inputs to a trained scoring algorithm in the next step.The listed kinematic features for the sensors above are intended to beexemplary, and not limiting; other types of sensors will producedifferent data from which different sets of features may be extracted.

The trained scoring algorithm used to process the kinematic featuresextracted from the movement data may comprise, for example, one or moreof a simple or multiple linear regression, an artificial neural network,a Bayesian network, or a genetic algorithm. The output of the trainedscoring algorithm may be a single score or multiple scores of any scale;a single score on the same scale as that of the UPDRS may be preferredin certain applications where simplicity or familiarity is the paramountconcern, while more sophisticated scores and scales may be preferred forother advanced applications, such as those that involve recommendationsfor treatment or closed-loop automated treatment delivery.

In various embodiments, following the step of symptom quantification, aseparate tuning algorithm may compute suggested changes to the therapysystem parameter settings based on the result of the symptomquantification algorithm and known or predicted current therapy systemparameter settings and physiological models.

Depending on the embodiment of the invention, the current therapy systemparameter settings changes may be input into the algorithm by a softwareuser interface (integrated tuning), or may be automatically sensed andinput from the DBS parameter settings by communicating with a DBSimplant or its programmer device or unit (intelligent tuning), or may beknown because the DBS parameter settings have been preset to some knownbaseline settings or restored to a previously saved settings preset. Theexisting parameter settings might also be predicted or derived based,for example, on observed or measured therapy effectiveness. Suggestedtherapy system parameter settings changes are then input into thetherapy system, and their effectiveness is measured using theabove-described method of symptom quantification.

The process of tuning therapy system parameter settings may remainiterative, but the present invention significantly minimizes, or atleast greatly reduces the time and expertise required to arrive atoptimized stimulation or therapy parameter settings, advantageouslyallowing clinicians, technicians or physicians with lesser training orexperience to adjust parameter settings during patient visits, and to doso in less time than is currently required. Additionally, the presentinvention increases access to geographically disparate populations byputting the expertise into the system and reducing or eliminating theneed for an expert or trained clinician to be present with each subject.

Many embodiments of the present invention utilize a remote tuning oradjustment system. In such embodiments, at least one electroniccomponent for transmitting and receiving signals is required. In suchembodiments, data corresponding to the subject's measured and quantifiedmovement and symptom data may be collected by the movement disorderdiagnostic device and transmitted using the at least one electroniccomponent for transmitting signals to a remote location or remotelocations. The data may be transmitted to a clinical center or locationwhere a clinician, physician or technician can view the data. In suchembodiments, the clinician, physician or technician can then make adecision and determination regarding a second level of therapy settingsthat should be applied to the subject's therapy device. Alternatively orin addition, an algorithm may be used to provide the determination as tothe second level of therapy parameters to be applied to the subject'stherapy device, and a clinician, physician or technician may optionallyreview the settings determined by the algorithm. In the remote tuning oradjustment embodiments, once a determination as to a second or nextlevel of therapy parameters is made, this second or next level ofparameters is then transmitted back to the subject's therapy devicewhere it is received by at least on electronic component for receivingsignals. In still other remote embodiments, a tuning algorithm, asdescribed below, of the movement disorder diagnostic device may providesuggested or determined second or next levels of therapy parameters, andin such embodiments the movement data and/or such suggested ordetermined parameters may be transmitted to storage or other remotelocations as described. Additionally, the movement data and/or second ornext level of therapy parameters may additionally be transmitted to acentral server, cloud based server, or other such database for storageand backup purposes.

Many embodiments of the present invention include optimization or tuningalgorithm(s) which are used to determine or recommend optimum therapysettings or parameters. Such optimization algorithms may include, butare not limited to simplex algorithms, extensions of the simplexalgorithm designed for quadratic and/or linear function programming,combinatorial algorithms, and other multi-variant optimizationalgorithms known to those in the art. In order to determine what adesired or optimal level of therapy parameters might be, the subject'ssymptoms or side effects must first be measured and quantified. Themeasurement and quantification preferably take place while the subjectis performing at least one movement disorder test as instructed. Oncethe initial measurement and quantification has been obtained, the systemand/or, in some embodiments a clinician, physician or technician,programs a second level of therapy parameters into the subject's therapydevice, and the subject repeats the movement disorder test(s) while thesymptoms or side effects are again measured and quantified. This processis repeated until the desired result(s), goals or constraints areachieved. These processes and steps are described in greater detailbelow. Preferably, whether obtaining optimized therapy parameters orsettings, or when iteratively testing to determine a second level oftherapy parameters, preferably, the subject is instructed to perform,and performs, at least 1 movement disorder test, where the testcomprises at least one task related to the subject's external bodymotion. More preferably, the subject is instructed to perform, andperforms, at least 2 movement disorder tests. Still more preferably, thesubject is instructed to perform, and performs, at least 3 movementdisorder tests. Yet more preferably, the subject is instructed toperform, and performs, at least 4 movement disorder tests. Even morepreferably, the subject is instructed to perform, and performs, at least5 movement disorder tests. Still yet more preferably, the subject isinstructed to perform, and performs, at least 6 movement disorder tests.Even still more preferably, the subject is instructed to perform, andperforms, at least 7 movement disorder tests.

Optimization of stimulation or therapy parameters or settings can bedescribed in reference to various constraints or desired results. Insome embodiments, optimization, or the level of parameters or settingselected based at least in part on movement disorder tests, results andscores refers to a reduction or minimization of symptom occurrenceand/or severity. Preferably in such embodiments, an optimized or secondlevel of therapy parameters or settings corresponds to at least a 10%reduction in the occurrence and/or severity of the subject's symptomswhile the subject is receiving therapy or is under the effects ofrecently received therapy. More preferably, an optimized or second levelof therapy parameters or settings corresponds to at least a 20%reduction in the occurrence and/or severity of the subject's symptomswhile the subject is receiving therapy or is under the effects ofrecently received therapy. Yet more preferably, an optimized or secondlevel of therapy parameters or settings corresponds to at least a 30%reduction in the occurrence and/or severity of the subject's symptomswhile the subject is receiving therapy or is under the effects ofrecently received therapy. Still more preferably, an optimized or secondlevel of therapy parameters or settings corresponds to at least a 40%reduction in the occurrence and/or severity of the subject's symptomswhile the subject is receiving therapy or is under the effects ofrecently received therapy. Even more preferably, an optimized or secondlevel of therapy parameters or settings corresponds to at least a 50%reduction in the occurrence and/or severity of the subject's symptomswhile the subject is receiving therapy or is under the effects ofrecently received therapy. Still yet more preferably, an optimized orsecond level of therapy parameters or settings corresponds to at least a60% reduction in the occurrence and/or severity of the subject'ssymptoms while the subject is receiving therapy or is under the effectsof recently received therapy. Even yet more preferably, an optimized orsecond level of therapy parameters or settings corresponds to at least a70% reduction in the occurrence and/or severity of the subject'ssymptoms while the subject is receiving therapy or is under the effectsof recently received therapy. Yet still more preferably, an optimized orsecond level of therapy parameters or settings corresponds to at least a75% reduction in the occurrence and/or severity of the subject'ssymptoms while the subject is receiving therapy or is under the effectsof recently received therapy. Even still more preferably, an optimizedor second level of therapy parameters or settings corresponds to atleast an 80% reduction in the occurrence and/or severity of thesubject's symptoms while the subject is receiving therapy or is underthe effects of recently received therapy. Yet even more preferably, anoptimized or second level of therapy parameters or settings correspondsto at least an 85% reduction in the occurrence and/or severity of thesubject's symptoms while the subject is receiving therapy or is underthe effects of recently received therapy. Still even more preferably, anoptimized or second level of therapy parameters or settings correspondsto at least a 90% reduction in the occurrence and/or severity of thesubject's symptoms while the subject is receiving therapy or is underthe effects of recently received therapy. Yet still even morepreferably, an optimized or second level of therapy parameters orsettings corresponds to at least a 95% reduction in the occurrenceand/or severity of the subject's symptoms while the subject is receivingtherapy or is under the effects of recently received therapy. Mostpreferably, an optimized or second level of therapy parameters orsettings corresponds to substantially eliminating the occurrence and/orseverity of the subject's symptoms while the subject is receivingtherapy or is under the effects of recently received therapy.

In other embodiments, optimization, or the level of parameters orsetting selected based at least in part on movement disorder tests,results and scores refers to a reduction or minimization of side effectoccurrence and or severity. Side effects may be a result ofpharmaceutical therapy (medication) the subject is receiving to treathis or her movement disorders, or from the stimulation therapy (e.g.,DBS). Preferably in such embodiments, an optimized or second level oftherapy parameters or settings corresponds to at least a 10% reductionin the occurrence and/or severity of the subject's side effects whilethe subject is receiving therapy or is under the effects of recentlyreceived therapy. More preferably, an optimized or second level oftherapy parameters or settings corresponds to at least a 20% reductionin the occurrence and/or severity of the subject's side effects whilethe subject is receiving therapy or is under the effects of recentlyreceived therapy. Yet more preferably, an optimized or second level oftherapy parameters or settings corresponds to at least a 30% reductionin the occurrence and/or severity of the subject's side effects whilethe subject is receiving therapy or is under the effects of recentlyreceived therapy. Still more preferably, an optimized or second level oftherapy parameters or settings corresponds to at least a 40% reductionin the occurrence and/or severity of the subject's side effects whilethe subject is receiving therapy or is under the effects of recentlyreceived therapy. Even more preferably, an optimized or second level oftherapy parameters or settings corresponds to at least a 50% reductionin the occurrence and/or severity of the subject's side effects whilethe subject is receiving therapy or is under the effects of recentlyreceived therapy. Still yet more preferably, an optimized or secondlevel of therapy parameters or settings corresponds to at least a 60%reduction in the occurrence and/or severity of the subject's sideeffects while the subject is receiving therapy or is under the effectsof recently received therapy. Even yet more preferably, an optimized orsecond level of therapy parameters or settings corresponds to at least a70% reduction in the occurrence and/or severity of the subject's sideeffects while the subject is receiving therapy or is under the effectsof recently received therapy. Yet still more preferably, an optimized orsecond level of therapy parameters or settings corresponds to at least a75% reduction in the occurrence and/or severity of the subject's sideeffects while the subject is receiving therapy or is under the effectsof recently received therapy. Even still more preferably, an optimizedor second level of therapy parameters or settings corresponds to atleast an 80% reduction in the occurrence and/or severity of thesubject's side effects while the subject is receiving therapy or isunder the effects of recently received therapy. Yet even morepreferably, an optimized or second level of therapy parameters orsettings corresponds to at least an 85% reduction in the occurrenceand/or severity of the subject's side effects while the subject isreceiving therapy or is under the effects of recently received therapy.Still even more preferably, an optimized or second level of therapyparameters or settings corresponds to at least a 90% reduction in theoccurrence and/or severity of the subject's side effects while thesubject is receiving therapy or is under the effects of recentlyreceived therapy. Yet still even more preferably, an optimized or secondlevel of therapy parameters or settings corresponds to at least a 95%reduction in the occurrence and/or severity of the subject's sideeffects while the subject is receiving therapy or is under the effectsof recently received therapy. Most preferably, an optimized or secondlevel of therapy parameters or settings corresponds to substantiallyeliminating the occurrence and/or severity of the subject's side effectswhile the subject is receiving therapy or is under the effects ofrecently received therapy.

Preferably, where the desired result is to reduce or minimize thesubject's movement disorder symptoms, the optimized or second level oftherapy parameters results in a reduction or minimization of at least 1movement disorder symptom. More preferably, the optimized or secondlevel of therapy parameters results in a reduction or minimization of atleast 2 movement disorder symptoms. Still more preferably, the optimizedor second level of therapy parameters results in a reduction orminimization of at least 3 movement disorder symptoms. Yet morepreferably, the optimized or second level of therapy parameters resultsin a reduction or minimization of at least 4 movement disorder symptoms.Even more preferably, the optimized or second level of therapyparameters results in a reduction or minimization of at least 5 movementdisorder symptoms.

Preferably, where the desired result is to reduce or minimize thesubject's side effects from medication or therapy, the optimized orsecond level of therapy parameters results in a reduction orminimization of at least 1 side effect. More preferably, the optimizedor second level of therapy parameters results in a reduction orminimization of at least 2 side effects. Still more preferably, theoptimized or second level of therapy parameters results in a reductionor minimization of at least 3 side effects. Yet more preferably, theoptimized or second level of therapy parameters results in a reductionor minimization of at least 4 side effects. Even more preferably, theoptimized or second level of therapy parameters results in a reductionor minimization of at least 5 side effects.

Other secondary constraints or desired results may also be consideredwhen optimizing or determining a second level of therapy parameters orsettings such as maximizing the battery life of the therapeutic (e.g.,DBS) device, maximizing the therapeutic window, and the like. Suchconstraints or desired results as these are secondary only in that theprimary goal of the therapy is to increase the subject's quality of lifeby reducing or minimizing symptoms or side effects, or balancing both,while also trying to improve the duration and quality of therapyotherwise. For example, maximizing battery life of the therapy devicehelps to increase the time required between subject's visits to theclinician, physician or technician as well as ensuring that the devicehas sufficient power and capability to effectively provide thedetermined levels of therapy. Similarly with maximizing the therapeuticwindow, which also increases the time between visits, but also maximizesthe length of time that the stimulation therapy has a positive effect onthe subject and reducing the number of stimulations required to achievethe desired results. Typically, the subject and his or her clinician,physician or technician will agree upon the primary desired result, suchas minimizing symptoms, but numerous other such constraints will also beconsidered, weighed and balanced in determining the optimized or secondlevel of parameters or settings.

Several embodiments may include a general optimization strategy in whichcombinations of the above desired results or constraints are used toselect the appropriate optimized settings. For example, such embodimentsmay optimize based on reducing or minimizing both symptoms and sideeffects. Any combination of type and/or number of desired results orconstraints may be used to optimize the system. Preferably, at least twodifferent desired results or constraints are considered when determiningan optimized group of therapy settings or parameters. More preferably,at least three different desired results or constraints are consideredwhen determining an optimized group of therapy settings or parameters.Still more preferably, at least four different desired results orconstraints are considered when determining an optimized group oftherapy settings or parameters. Yet more preferably, at least fivedifferent desired results or constraints are considered when determiningan optimized group of therapy settings or parameters. Even morepreferably, at least six different desired results or constraints areconsidered when determining an optimized group of therapy settings orparameters. Most preferably, more than seven different desired resultsor constraints are considered when determining an optimized group oftherapy settings or parameters.

Numerous embodiments of the present invention are envisioned in thisdisclosure. These following embodiments are examples of the manyembodiments encompassed by the present invention, but do not in any waylimit the many other embodiments covered by this disclosure.

One embodiment of the present invention includes a method of tuning amovement disorder therapy system comprising steps of providing amovement disorder diagnostic device to a subject having a deep brainstimulation (DBS) device with a first level of DBS parameters, themovement disorder diagnostic device comprising at least onephysiological or movement sensor having a signal, and a processorcomprising an algorithm, instructing the subject to perform at least onemovement disorder test(s) while the subject is undergoing DBS therapy oris under the effects of DBS therapy, measuring and quantifying motorsymptoms of the subject based at least in part on the signal from the atleast one physiological or movement sensor(s) during the at least onemovement disorder test(s), entering data corresponding to the subject'smeasured and quantified motor symptoms into an algorithm, providing,with the algorithm, a second level of DBS parameters based at least inpart on the data entered into the algorithm, and entering the secondlevel of DBS parameters into the subject's DBS device such that thesubject's DBS device operates under the second level of DBS parameters.

Another embodiment of the present invention includes a method of tuninga movement disorder therapy system comprising steps of providing amovement disorder diagnostic device to a subject having a deep brainstimulation (DBS) device with a first level of DBS parameters, themovement disorder diagnostic device comprising at least onephysiological or movement sensor having a signal, and a processorcomprising an algorithm, instructing the subject to perform at least onemovement disorder test(s) while the subject is undergoing DBS therapy oris under the effects of DBS therapy, measuring and quantifying motorsymptoms of the subject based at least in part on the signal from the atleast one physiological or movement sensor(s) during the at least onemovement disorder test(s), entering data corresponding to the subject'smeasured and quantified motor symptoms into an algorithm, determining,with the algorithm, at least two optional groups of DBS parameters, eachoptional group of parameters corresponding to a different desiredoutcome or constraint, selecting one of the at least two optional groupsof DBS parameters, and entering the selected optional group of DBSparameters into the subject's DBS device such that the subject's DBSdevice operates under the second level of DBS parameters.

Still yet another embodiment of the present invention includes a methodof tuning a movement disorder therapy system comprising steps ofproviding a movement disorder diagnostic device to a subject having adeep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, and a processorcomprising an algorithm, instructing the subject to perform at least onemovement disorder test(s) while the subject is undergoing DBS therapy oris under the effects of DBS therapy, measuring and quantifying motorsymptoms of the subject based at least in part on the signal from the atleast one physiological or movement sensor(s) during the at least onemovement disorder test(s), entering the data corresponding to thesubject's measured and quantified motor symptoms into an algorithm,determining, with the algorithm, at least two optional groups of DBSparameters, each optional group of parameters corresponding to adifferent desired outcome or constraint, transmitting data correspondingto the subject's measured and quantified motor symptoms and the at leasttwo optional groups of DB S parameters to a clinician, physician ortechnician—at a remote location, having the clinician, physician ortechnician select at least two of the at least two optional groups ofDBS parameters, combining the at least two selected optional groups ofDBS parameters into one set of combined DB S parameters, transmittingthe set of combined DB S parameters to the subject's DBS device, andentering the set of combined DBS parameters into the subject's DBSdevice such that the subject's DBS device operates under the secondlevel of DBS parameters.

Yet still another embodiment of the present invention includes a methodof tuning a movement disorder therapy system comprising steps ofproviding a movement disorder diagnostic device to a subject having adeep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, and a processorcomprising an algorithm, instructing the subject to perform at least onemovement disorder test(s) while the subject is undergoing DBS therapy oris under the effects of DBS therapy, measuring and quantifying motorsymptoms of the subject based at least in part on the signal from the atleast one physiological or movement sensor(s) during the at least onemovement disorder test(s), entering data corresponding to the subject'smeasured and quantified motor symptoms into an algorithm, determining,with the algorithm, at least two optional groups of DBS parameters, eachoptional group of parameters corresponding to a different desiredoutcome or constraint, transmitting data corresponding to the subject'smeasured and quantified motor symptoms and the at least two optionalgroups of DB S parameters to a clinician, physician or technician at aremote location, having the clinician, physician or technician selectone of the at least two optional groups of DBS parameters, anduploading, substantially simultaneously with transmitting, with at leastone electronic component the selected optional group of DBS parametersand/or measured and quantified motor symptoms to a database for storageand/or review by a clinician, technician or physician.

Even yet another embodiment of the present invention includes a methodof tuning a movement disorder therapy system comprising steps ofproviding a movement disorder diagnostic device to a subject having adeep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, and a processorcomprising an algorithm, instructing the subject to perform at least onemovement disorder test(s) while the subject is undergoing DBS therapy oris under the effects of DBS therapy, measuring and quantifying motorsymptoms of the subject based at least in part on the signal from the atleast one physiological or movement sensor(s) during the at least onemovement disorder test(s), entering data corresponding to the subject'smeasured and quantified motor symptoms into an algorithm, determining,with the algorithm, at least two optional groups of DBS parameters, eachoptional group of parameters corresponding to a different desiredoutcome or constraint, selecting one of the at least two optional groupsof DBS parameters, and uploading, substantially simultaneously withtransmitting, with at least one electronic component the second level ofDBS parameters and/or measured and quantified motor symptoms to adatabase for storage and/or review by a clinician, technician orphysician.

Yet still another embodiment of the present invention includes a methodof tuning a movement disorder therapy system comprising steps ofproviding a movement disorder diagnostic device to a subject having adeep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, and a processorcomprising an algorithm, instructing the subject to perform at least onemovement disorder test(s) while the subject is undergoing DBS therapy oris under the effects of DBS therapy, measuring and quantifying motorsymptoms of the subject based at least in part on the signal from the atleast one physiological or movement sensor(s) during the at least onemovement disorder test(s), entering data corresponding to the subject'smeasured and quantified motor symptoms into an algorithm, determining,with the algorithm, at least two optional groups of DBS parameters, eachoptional group of parameters corresponding to a different desiredoutcome or constraint, selecting at least two of the at least twooptional groups of DBS parameters, combining the at least two selectedoptional groups of DBS parameters into one set of combined DBSparameters, and uploading, substantially simultaneously withtransmitting, with at least one electronic component the second level ofDBS parameters and/or measured and quantified motor symptoms to adatabase for storage and/or review by a clinician, technician orphysician.

Yet even still another embodiment of the present invention includes amethod of tuning a movement disorder therapy system comprising steps ofproviding a movement disorder diagnostic device to a subject having adeep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, and a processorcomprising an algorithm, displaying on a programming device a list ofactivities, actions or tasks for the subject to select from, having thesubject elect at least one activity, action or task from the list on theprogramming device, selecting with the movement disorder diagnosticdevice a predetermined set of DBS parameters corresponding to theelected at least one activity, action or task, entering with theprogramming device the group of selected DBS parameters corresponding tothe at least one elected activity, action or task into the subject's DBSdevice such that the subject's DBS device operates under the selectedgroup of DBS parameters, measuring and quantifying motor symptoms of thesubject based at least in part on the signal from the at least onephysiological or movement sensor(s) while the subject performs the atleast one elected activity, action or task, entering data correspondingto the subject's measured and quantified motor symptoms into analgorithm, providing, with the algorithm, a second level of DBSparameters based at least in part on the data entered into thealgorithm, the second level of DBS parameters maximizing the subject'sability to perform the at least one elected activity, action or task,transmitting data corresponding to the subject's measured and quantifiedmotor symptoms and the second level of DBS parameters to a clinician,physician or technician at a remote location, having the clinician,physician or technician approve or edit the second level of DBSparameters provided by the algorithm, transmitting the approved oredited second level of DBS parameters to the subject's DBS device, andentering the second level of DBS parameters into the subject's DBSdevice such that the subject's DBS device operates under the secondlevel of DBS parameters while the subject performs the at least oneelected activity, action or task.

Still even another embodiment of the present invention includes a methodof tuning a movement disorder therapy system comprising steps ofproviding a movement disorder diagnostic device to a subject having adeep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, and a processorcomprising an algorithm, instructing the subject to perform at least onemovement disorder test(s) while the subject is undergoing DBS therapy oris under the effects of DBS therapy, measuring and quantifying motorsymptoms of the subject based at least in part on the signal from the atleast one physiological or movement sensor(s) during the at least onemovement disorder test(s), entering the data corresponding to thesubject's measured and quantified motor symptoms into an algorithm,providing, with the algorithm, a second level of DBS parameters based atleast in part on the data entered into the algorithm, transmitting datacorresponding to the subject's measured and quantified motor symptomsand the second level of DBS parameters to a clinician, physician ortechnician at a remote location, having the clinician, physician ortechnician approve or edit the second level of DBS parameters providedby the algorithm, transmitting the approved or edited second level ofDBS parameters to the subject's DBS device, and automatically enteringthe second level of DBS parameters into the subject's DBS device suchthat the subject's DBS device operates under the second level of DBSparameters.

Even still another embodiment of the present invention includes a methodof tuning a movement disorder therapy system comprising steps of havinga subject wear a movement disorder diagnostic device, the subject havinga deep brain stimulation (DBS) device with a first level of DBSparameters, and the movement disorder diagnostic device comprising atleast one physiological or movement sensor having a signal, identifyingor determining what activity, movement or motion the subject isperforming, identifying or determining motor symptoms of a movementdisorder or side effects of a treatment the subject is undergoing thatthe subject is suffering or has suffered based at least in part on thesignal(s) from the at least one physiological or movement sensor and atleast in part on the identified or determined activity, movement ormotion, measuring and quantifying the identified or determined motorsymptoms or side effects with a processor based at least in part on thesignal(s) from the at least one physiological or movement sensor whilethe subject is wearing the diagnostic device, entering datacorresponding to the measured and quantified motor symptoms or sideeffects into the processor, the processor comprising an algorithm,calculating, with the processor, a second level of DBS parameters basedat least in part on the data entered into the processor, transmittingthe second level of DBS parameters to the subject's DBS device, andentering the second level of DBS parameters into the subject's DBSdevice such that the subject's DBS device operates under the calculatedsecond level of DBS parameters.

Even still yet another embodiment of the present invention includes amethod of tuning a movement disorder therapy system comprising steps ofhaving a subject wear a movement disorder diagnostic device, the subjecthaving a deep brain stimulation (DBS) device with a first level of DBSparameters, and the movement disorder diagnostic device comprising atleast one physiological or movement sensor having a signal, identifyingor determining what activity, movement or motion the subject isperforming, identifying or determining motor symptoms of a movementdisorder or side effects of a treatment the subject is undergoing thatthe subject is suffering or has suffered based at least in part on thesignal(s) from the at least one physiological or movement sensor and atleast in part on the identified determined activity, movement or motion,measuring and quantifying the identified or determined motor symptoms orside effects with a processor based at least in part on the signal(s)from the at least one physiological or movement sensor while the subjectis wearing the diagnostic device, entering data corresponding to themeasured and quantified motor symptoms or side effects into theprocessor, the processor comprising an algorithm, calculating, with theprocessor, at least two optional groups of DBS parameters based at leastin part on the data entered into the processor, each optional groupaddressing a separate identified or detected symptom or side effect,having the subject select one optional group of DBS parameters based onthe subject's activity, movement or motion, transmitting the selectedoptional group of DBS parameters to the subject's DBS device, andentering the selected optional group of DBS parameters into thesubject's DBS device such that the subject's DBS device operates underthe selected optional group of DBS parameters.

Yet even still another embodiment of the present invention includes amethod of tuning a movement disorder therapy system comprising steps ofhaving a subject wear a movement disorder diagnostic device, the subjecthaving a deep brain stimulation (DBS) device with a first level of DBSparameters, and the movement disorder diagnostic device comprising atleast two physiological or movement sensors, each having a signal,identifying or determining what activity, movement or motion the subjectis performing, identifying or determining motor symptoms of a movementdisorder or side effects of a treatment that the subject is undergoingthat the subject is suffering or has suffered based at least in part onthe signals from the at least two physiological or movement sensors, andat least in part on the identified or determined activity, movement ormotion, measuring and quantifying the identified or determined motorsymptoms or side effects with a processor based at least in part on thesignals from the at least two physiological or movement sensors and theidentified or determined symptoms or side effects while the subject iswearing the diagnostic device, entering data corresponding to themeasured and quantified motor symptoms or side effects into theprocessor, the processor comprising an algorithm, calculating, with theprocessor, a second level of DBS parameters based at least in part onthe data entered into the algorithm, transmitting the second level ofDBS parameters to the subject's DBS device, and entering the secondlevel of DBS parameters into the subject's DBS device such that thesubject's DBS device operates under the second level of DBS parameters,wherein the second level of DBS parameters is an optimization ofparameters addressing or treating to some degree each of the identifiedor determined symptoms or side effects based on the identified ordetermined activity, movement or motion.

Still even yet another embodiment of the present invention includesmethod of adjusting a treatment or therapy device to reduce a subject'ssymptoms of a movement disorder or side effects of treatment or therapyof a subject's movement disorder provided by the treatment or therapydevice, the method comprising steps of: measuring a subject's brainactivity during a first time period; simultaneously measuring during thefirst time period the subject's movement disorder symptoms or sideeffects of treatment or therapy of the subject's movement disorder;changing parameters of the subject's treatment or therapy; measuring thesubject's brain activity during a second time period; simultaneouslymeasuring during the second time period the subject's movement disordersymptoms or side effects of treatment or therapy of the subject'smovement disorder; determining the brain activity that minimizes themeasured symptoms or side effects by correlating the measured symptomsor side effects with the simultaneously measured brain activity to mapthe part(s) of the subject's brain responsible for the symptoms or sideeffects; training a tuning algorithm comprised in a processor based onthe determined brain activity that minimizes the measured symptoms orside effects; calculating, with the tuning algorithm, a suggested set oftreatment or therapy parameters based at least in part on the measuredbrain activity and measured symptoms or side effects, the suggested setof parameters adapted to be reviewed and approved by a clinician,physician, or technician; and entering approved treatment or therapyparameters into the treatment or therapy device such that the treatmentor therapy device provides treatment or therapy to the subject based onthe approved parameters.

Even yet still another embodiment of the present invention includes amethod of adjusting a treatment or therapy device to reduce a subject'ssymptoms of a movement disorder or side effects of treatment or therapyof a subject's movement disorder provided by the treatment or therapydevice, the method comprising steps of: measuring a subject's brainactivity during a first time period; simultaneously measuring during thefirst time period the subject's movement disorder symptoms or sideeffects of treatment or therapy of the subject's movement disorder;changing parameters of the subject's treatment or therapy; measuring thesubject's brain activity during a second time period; simultaneouslymeasuring during the second time period the subject's movement disordersymptoms or side effects of treatment or therapy of the subject'smovement disorder; determining the brain activity that minimizes themeasured symptoms or side effects by correlating the measured symptomsor side effects with the simultaneously measured brain activity to mapthe part(s) of the subject's brain responsible for the symptoms or sideeffects; training a tuning algorithm comprised in a processor based onthe determined brain activity that minimizes the measured symptoms orside effects; calculating, with the tuning algorithm, a suggested set oftreatment or therapy parameters based at least in part on the measuredbrain activity and measured symptoms or side effects; and entering thesuggested set of treatment or therapy parameters into the treatment ortherapy device such that the treatment or therapy device providestreatment or therapy to the subject based on the suggested set ofparameters.

Yet still even another embodiment of the present invention includes amethod of adjusting a treatment or therapy device to reduce a subject'ssymptoms of a movement disorder or side effects of treatment or therapyof a subject's movement disorder provided by the treatment or therapydevice, the method comprising steps of: measuring a subject's brainactivity during a first time period; simultaneously measuring during thefirst time period the subject's movement disorder symptoms or sideeffects of treatment or therapy of the subject's movement disorder;changing parameters of the subject's treatment or therapy; measuring thesubject's brain activity during a second time period; simultaneouslymeasuring during the second time period the subject's movement disordersymptoms or side effects of treatment or therapy of the subject'smovement disorder; determining the brain activity that minimizes themeasured symptoms or side effects by correlating the measured symptomsor side effects with the simultaneously measured brain activity to mapthe part(s) of the subject's brain responsible for the symptoms or sideeffects; training a tuning algorithm comprised in a processor based onthe determined brain activity that minimizes the measured symptoms orside effects; measuring the subject's brain activity during a third timeperiod; calculating, with the tuning algorithm, a suggested set oftreatment or therapy parameters based at least in part on the brainactivity measured during the third time period; and entering thesuggested set of treatment or therapy parameters into the treatment ortherapy device such that the treatment or therapy device providestreatment or therapy to the subject based on the suggested set ofparameters.

Even yet still another embodiment of the present invention includes amethod of tuning a movement disorder therapy system comprising steps of:having a subject wear a movement disorder diagnostic device, the subjecthaving a deep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, the DBS devicecomprising at least one dual-mode DBS lead with at least one or aplurality of contacts adapted to provide electrical stimulation and toacquire physiological signals, each contact having a signal; measuringthe subject's external body motion with the at least one physiologicalor movement sensor; measuring the subject's brain activity substantiallysimultaneously with measuring the external body motion; identifying ordetermining motor symptoms of a movement disorder or side effects of atreatment the subject is undergoing that the subject is suffering or hassuffered based at least in part on the signal(s) from the at least onephysiological or movement sensor and at least in part on the signalsfrom the plurality of DBS lead contacts; measuring and quantifying theidentified or determined motor symptoms or side effects with a processorcomprising a scoring algorithm based at least in part on the signal(s)from the at least one physiological or movement sensor and at least inpart on the signals from the DBS lead contacts while the subject iswearing the diagnostic device; entering data corresponding to themeasured and quantified motor symptoms or side effects into theprocessor, the processor comprising a tuning algorithm; calculating,with the tuning algorithm, a second level of DB S parameters based atleast in part on the data entered into the processor; transmitting thesecond level of DBS parameters to the subject's DBS device; and enteringthe second level of DBS parameters into the subject's DBS device suchthat the subject's DBS device operates under the calculated second levelof DBS parameters.

Yet still even another embodiment of the present invention includes amethod of tuning a movement disorder therapy system comprising steps of:having a subject wear a movement disorder diagnostic device, the subjecthaving a deep brain stimulation (DBS) device with a first level of DBSparameters, the movement disorder diagnostic device comprising at leastone physiological or movement sensor having a signal, the DBS devicecomprising at least one dual-mode DBS lead with a plurality of contactsadapted to provide electrical stimulation and to acquire physiologicalsignals, each contact having a signal; identifying or determining whatactivity, movement or motion the subject is performing; measuring thesubject's external body motion with the at least one physiological ormovement sensor; measuring the subject's brain activity substantiallysimultaneously with measuring the external body motion; identifying ordetermining motor symptoms of a movement disorder or side effects of atreatment the subject is undergoing that the subject is suffering or hassuffered based at least in part on the signal(s) from the at least onephysiological or movement sensor, at least in art based on the signalsfrom the plurality of DBS lead contacts, and at least in part on theidentified determined activity, movement or motion; measuring andquantifying the identified or determined motor symptoms or side effectswith a processor comprising a scoring algorithm based at least in parton the signal(s) from the at least one physiological or movement sensorand at least in part on the signals from the DBS lead contacts while thesubject is wearing the diagnostic device; entering data corresponding tothe measured and quantified motor symptoms or side effects into theprocessor, the processor comprising a tuning algorithm; calculating,with the tuning algorithm, a second level of DBS parameters based atleast in part on the data entered into the processor; transmitting thesecond level of DBS parameters to the subject's DBS device; and enteringthe second level of DBS parameters into the subject's DBS device suchthat the subject's DBS device operates under the calculated second levelof DBS parameters.

Still even yet another embodiment of the present invention includes amethod of tuning a movement disorder therapy system comprising steps of:providing to the subject a deep brain stimulation (DBS) device with afirst level of DBS parameters, the DBS device comprising at least onedual-mode DBS lead with a plurality of contacts adapted to provideelectrical stimulation and to acquire physiological signals, eachcontact having a signal; measuring the subject's brain activitysubstantially simultaneously with measuring the external body motion;identifying or determining motor symptoms of a movement disorder or sideeffects of a treatment the subject is undergoing that the subject issuffering or has suffered based at least in part on the signals from theplurality of DBS lead contacts; measuring and quantifying the identifiedor determined motor symptoms or side effects with a processor comprisinga scoring algorithm based at least in part on the signals from the DBSlead contacts while the subject is wearing the diagnostic device;entering data corresponding to the measured and quantified motorsymptoms or side effects into the processor, the processor comprising atuning algorithm; calculating, with the tuning algorithm, a second levelof DB S parameters based at least in part on the data entered into theprocessor; transmitting the second level of DBS parameters to thesubject's DBS device; and entering the second level of DBS parametersinto the subject's DBS device such that the subject's DBS deviceoperates under the calculated second level of DBS parameters.

Still another embodiment of the present invention includes a method ofreducing a subject's symptoms of a movement disorder or side effects oftreatment of a subject's movement disorder comprising steps of:measuring a subject's movement disorder symptoms or side effects oftreatment or therapy of the subject's movement disorder during a firsttime period; simultaneously measuring a subject's brain activity duringthe first time period; obtaining a first symptom brain activity map bycorrelating the first time period measured symptoms or side effects withthe first time period measured brain activity; providing treatment tothe subject; measuring a subject's movement disorder symptoms or sideeffects of treatment or therapy of the subject's movement disorderduring a second time period; simultaneously measuring a subject's brainactivity during the second time period; obtaining a second symptom brainactivity map by correlating the second time period measured symptoms orside effects with the second time period measured brain activity;changing parameters of the treatment provided to the subject based atleast in part on the differences between the first and second brainactivity maps to reduce the measured symptoms or side effects.

Yet another embodiment of the present invention includes a method oftuning a movement disorder therapy system comprising steps of: providinga movement disorder diagnostic device (M3D) to a subject having a deepbrain stimulation (DBS) device with treatment parameters, the M3Dcomprising at least one external physiological or movement sensor havinga signal, and at least one brain activity sensor having a signal;simultaneously measuring with the M3D, during a first time period, brainactivity and symptoms of the subject's movement disorder or side effectsof treatment of the movement disorder; changing the first level of DBSparameters based at least in part on the measured brain activity andsymptoms or side effects; simultaneously measuring with the M3D, duringa second time period, brain activity and symptoms of the subject'smovement disorder or side effects of treatment of the movement disorder;determining brain activity that minimizes the measured symptoms or sideeffects; training a tuning algorithm based at least in part on thedetermination of brain activity that minimizes the measured symptoms orside effects; and adjusting the treatment parameters of the subject'sDBS device to achieve the brain activity determined to minimize themeasured symptoms or side effects.

It is to be understood that both the foregoing general description andthe following detailed description are merely exemplary of theinvention, and are intended to provide an overview or framework forunderstanding the nature and character of the invention as it isclaimed. The accompanying drawings are included to provide a furtherunderstanding of the invention, and are incorporated in and constitute apart of this specification. The drawings illustrate various embodimentsof the invention and together with the description serve to explain theprinciples and operation of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 . Schematic view of a subject undergoing post-surgical DBSadjustment with one embodiment of the invention involving automatedinstruction of the subject and electronic transmission between thesystem and the subject's DBS device.

FIG. 2 . Schematic view of a subject undergoing post-surgical DBSadjustment with another embodiment of the invention involving electronictransmission between the system and the subject's DBS device.

FIG. 3 . Flow diagram of a parameter adjustment suggestion algorithm insome embodiments of the present invention.

FIG. 4 . Flow diagram of an artificial neural network of the parameteradjustment suggestion algorithm in some embodiments of the presentinvention.

FIG. 5 . Graphic depiction of display pages displaying test results andscores, one embodiment of a tuning map, as well as one embodiment of aparameter input screen.

FIG. 6 . Graphic depiction of one embodiment of tuning maps used todisplay test results and symptom severity objectively measured by thesystem and displayed as a scatter plot of symptom severity scores.

FIG. 7 . Illustration of the subject screening process to determine ifDBS is a viable option for a particular subject.

FIG. 8 . Illustration of various embodiments of the DBS parameterprogramming/tuning process.

FIG. 9A-B. Illustration depicting the difference between different DBSlead configurations including (A) monopolar DBS lead configurationswhich do not allow shaping of the electrical stimulation field, and (B)bipolar DBS lead configurations which are able to shape the electricalstimulation field to avoid activating a side effect region of the brain.

FIG. 10 . One embodiment of an interface device allowing a user toselect an activity to perform, and which can change the subject'stherapy parameters or settings based on the selected activity.

FIG. 11 . Flow chart describing a method embodiment wherein the systemidentifies an activity the subject is performing and any motor symptomsor side effects the subject is experiencing, then measures andquantifies the symptoms or side effects, calculates a second level oftherapy parameters, and enters the updated parameters into the subjectstherapy device.

FIG. 12 . Flow chart describing a method embodiment wherein the systemidentifies an activity the subject is performing and any motor symptomsor side effects the subject is experiencing, then measures andquantifies the symptoms or side effects, calculates at least twooptional groups of therapy parameters, at least one of which is selectedby the subject to be used, and the system enters the selected parametersinto the subjects therapy device.

FIG. 13 . Flow chart describing a method embodiment wherein the systemidentifies an activity the subject is performing and any motor symptomsor side effects the subject is experiencing, then measures andquantifies the symptoms or side effects, calculates a second level oftherapy parameters, and enters the updated parameters into the subjectstherapy device, where the updated parameters are optimized to addresseach of the identified activity and symptoms and side effects.

FIG. 14 . Flow chart describing one programming option embodiment of thepresent invention wherein an algorithm(s) provides a recommended set ofparameters or settings to be reviewed and approved by a clinician at aremote location before those parameters or settings are programmed intothe subject's therapy device.

FIG. 15 . Flow chart depicting a start-to-finish description of theprocess from the subject exhibiting movement disorder symptoms throughtreatment and therapy of those movement disorder symptoms, and where thesubject's therapy device is programmed newly determined therapyparameters or settings.

FIG. 16 . Flow chart of one exemplary embodiment of an intelligenttuning algorithm for determining or selecting a second set or group oftherapy parameters or settings based on measured and quantified movementdata and/or movement disorder and various constraints.

FIG. 17 . Flow chart of one exemplary embodiment of an integrated tuningalgorithm for determining or selecting a second set or group of therapyparameters or settings based on measured and quantified movement dataand/or movement disorder and various constraints where a clinician at aremote location determines the second group which is then transmitted tothe subject's device.

FIG. 18 . Flow chart of one exemplary embodiment of an integrated tuningalgorithm for determining or selecting a second set or group of therapyparameters or settings based on measured and quantified movement dataand/or movement disorder and various constraints where a clinician at aremote location determines at least two optional groups, only one ofwhich is selected for use, and the selected group is then transmitted tothe subject's device.

FIG. 19 . Flow chart of one exemplary embodiment of an integrated tuningalgorithm for determining or selecting a second set or group of therapyparameters or settings based on measured and quantified movement dataand/or movement disorder and various constraints where a clinician at aremote location determines the second group which is then transmitted tothe subject's device and the group is entered automatically into thesubject's device no direct interaction between the clinician and thesubject's therapy device.

FIG. 20 . Flow chart of one exemplary embodiment of an integrated tuningalgorithm for determining or selecting a second set or group of therapyparameters or settings based on measured and quantified movement dataand/or movement disorder and various constraints where a clinician at aremote location determines the second group which is then transmitted tothe subject's device, and where the therapy parameters or settingsand/or the quantified motor symptom data is transmitted to a databasefor storage and/or access by a clinician.

FIG. 21 . Image depicting a typical human brain labeled with the variouslobes and cortexes known and identified.

FIG. 22 . Image depicting a traditional map of the human brain motorcortex correlated with known regions of body controlled by particularportions of the motor cortex.

FIG. 23 . Flow chart describing a method embodiment wherein the systemidentifies an activity the subject is performing and any motor symptomsor side effects the subject is experiencing and correlates thosemovements and symptoms to measured brain activity, then measures andquantifies the symptoms or side effects, calculates a second level oftherapy parameters, and enters the updated parameters into the subject'stherapy device.

FIG. 24 . Flow chart describing a method embodiment wherein the systemidentifies an activity, movement or motion the subject is performing andany motor symptoms or side effects the subject is experiencing based ondetected and/or measured brain activity, then measures and quantifiesthe symptoms or side effects, calculates a second level of therapyparameters, and enters the updated parameters into the subject's therapydevice.

FIG. 25 . Flow chart depicting an embodiment of the testing andmeasurement process for obtaining data related to a subject's externalbody movement or motion and/or physiological data and correlating suchwith measured brain activity to map the areas of the subject's brainrelated to particular types of motion.

FIGS. 26A-B. Images depicting mapped brain activity related toparticular types of body motion, specifically for A) arm movements andB) leg movements.

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to methods for semi-automatically andautomatically adjusting, or tuning, treatment parameters in movementdisorder therapy systems either in a location separate from the patients(remotely) or at the patient's location. Semi-automatic adjustmentincludes providing the clinician, physician or technician withobjective, quantitative or semi-quantitative data or measurementsrelated to a subject's movement disorder symptoms, determining desiredparameters, and then entering those parameters either manually,semi-automatically or automatically into the subject's device.Semi-automatic and automatic adjustment includes providing objective,quantitative or semi-quantitative data or measurements related to asubject's movement disorder symptoms to an algorithm, determiningdesired parameters using the algorithm, and then entering thoseparameters either semi-automatically (i.e., allowing clinician,physician or technician to accept the recommended adjustment to theparameters or settings) or automatically (i.e., parameters or settingsare approved and automatically transmitted and entered) into thesubject's therapy device. The present invention further relates to asystem for screening patients to determine if they are viable candidatesfor certain therapy modalities. The present invention still preferablyfurther provides methods of quantifying movement disorders for thetreatment of patients who exhibit symptoms of such movement disordersincluding, but not limited to, Parkinson's disease and Parkinsonism,Dystonia, Chorea, and Huntington's disease, Ataxia, Tremor and EssentialTremor, Tourette syndrome, stroke, and the like. The present inventionyet further relates to methods of automatically and intelligently tuninga therapy device using objective quantified movement disorder symptomdata acquired by a movement disorder diagnostic device with the therapysetting or parameters to be provided to the subject via his or hertherapy device.

The movement disorder diagnostic device, systems and/or methods of thevarious embodiments of the present invention preferably are used toscreen patients, analyze, score, and treat various disorders, andespecially movement disorders and mental health disorders. Movementdisorders for purposes of this application include but are not limitedto Parkinson's disease and Parkinsonism, Dystonia, Chorea, andHuntington's disease, Ataxia, Tremor and Essential Tremor, Tourettesyndrome, stroke, and the like. Mental health disorders include, but arenot limited to major depression, bipolar disorder, obsessive compulsivedisorder, and antisocial disorders. Some of the treatments used forthese disorders involve pharmaceutical interventions, fetal celltransplants, surgery, or deep brain stimulation. The efficacy of anintervention is often judged by the intervention's ability to alleviatesubject symptoms and improve subject quality of life. The subject onwhich the system or method is used is a human or another form of animal.

The movement disorder diagnostic device the various embodiments of thepresent invention are preferably portable. By portable it is meant amongother things that the device is capable of being transported relativelyeasily. Relative ease in transport means that the device can be carriedby a single person, generally in a carrying case to the point of use orapplication. Additionally, relative ease in transport means that thedevice is easily worn, carried by or attached to a subject. Furthermorethe device preferably should be relatively light-weight. By relativelylightweight, preferably the device weighs less than about 3 lbs., morepreferably less than about 2 lbs., even more preferably less than about1 lb., still more preferably less than about 0.5 lbs., still preferablyless than about 2 ounces and most preferably less than 0.5 ounces. Bybeing lightweight and further compact, the device should gain greateracceptance for use by the subject. The system for measuring andcalculating the severity of the symptoms including external computerspreferably weighs less than about 15 lbs., more preferably less thanabout 10 lbs., still more preferably less than about 5 lbs., even morepreferably less than about 2 lbs., and most preferably less than 0.5lbs. This system more preferably can fit in a reasonably sized carryingcase so the patient or their caregiver can easily transport the system.

Another advantage of the systems and methods of the present invention isoptionally the ability to determine or calculate the severity of asubject's symptoms in real time. Throughout this disclosure, by realtime it is meant that within 30 minutes of sensing and measurement theseverity of a subject's symptoms can be calculated or determined. Realtime, more preferably means that the subject's symptoms can becalculated or determined in less than about 30 seconds, more preferablyin less than about 1 second, even more preferably in less than about 0.1seconds, and most preferably in less than about 0.01 seconds.

The devices of the various embodiments of the present invention can formpart of a system for use by a physician, veterinarian, technician orclinician for analysis or evaluation of a subject's movement disorder;for pharmaceutical research, for adjustment of neurostimulation therapysuch as for example deep brain stimulation (DBS) or spinal cordstimulation (SCS), or for delivery of pharmaceutical compounds. Otherelements of this system may include but are not limited to receivers,routers, communication devices, processors, displays, drug deliverydevices and the like, some of which are described further in variousembodiments described in more detail below.

The preferable movement disorder diagnostic device, described in greaterdetail below, worn, carried by or attached to the subject, containsvarious physiological or movement sensor(s) used to measure thesubject's external body motion and/or other physiological signals fromthe subject's body. The movement disorder diagnostic device maytemporarily store the subject's movement or physiological data inonboard memory and/or transmit this data to an external device. In someembodiments, the movement disorder diagnostic device may directlytransmit the data to a centralized database, to multiple databases atthe same or multiple locations, or to a cloud-based database where thedata can be stored and accessed essentially immediately by authorizedusers who can analyze and/or further process the data, use it todiagnose or assess the subject's symptoms or disorders, or the like.Additionally, or alternatively, the movement disorder diagnostic devicecan transmit the movement or physiological data to an external computerdevice, or directly to a remote location for access by a clinician,physician or technician. Transmission to a remote location preferablymay include transmission directly to such a computer device at saidremote location, or may involve a user (such as a clinician, physicianor technician) at the remote location accessing the data or informationthrough the database or databases as described. The computer device,though called a tablet herein, is understood to be any type of deviceknown to those skilled in the art usable for the intended purpose(s) orfunction(s), including, but not limited to, desktop computers, laptopcomputers, tablet computers, personal digital assistants (PDAs, “smart”cellular telephones, and the like). The computer device, or tablet, maybe provided as part of the present invention's system, but in manyembodiments the movement disorder diagnostic device is designed to workwith and communicate with such devices of any third-party manufactureror provider who provides such devices for the intended function orpurpose of the present invention. In such cases, a software installationproviding the user interface, tuning map capabilities, diagnostic andanalysis tools, and the like would simply be installed on thethird-party computer device or tablet as software or an application (or“app”), or the interaction with the user(s) can be web based through aweb portal. The tuning map is one example of a tool that allows theclinician, physician or technician to review and/or determine the next,or preferably best (optimized) therapeutic settings or parameters forthe subject's therapy device, such as a DBS device. In the presentinvention, tuning maps are used primarily as a tool for review andanalysis of the automatically, intelligently generated parameters orsettings provided by a tuning algorithm, and not for full-time orregular interaction and programming by a clinician, physician ortechnician. The tuning maps are described in greater detail in U.S. Pat.Nos. 9,393,418 and 9,662,502, both of which are herein incorporated byreference. Once the next therapy parameters or settings have beendetermined, a programmer device or unit can be used to communicatedirectly with the therapy device. Again, the programmer device or unitmay be integrated into the subject-worn diagnostic device, a separateunit in and of itself, or may be part of the tablet or computer, andautomatically communicates the parameters or settings to the programmerdevice or unit or directly to the subject's therapy device.

As noted, various embodiments of the present invention may include asensor for measuring a subject's external body motion. The invention mayalso include at least one sensor for indirectly measuring movementmetrics. Many types of sensors are known by those skilled in the art formeasuring external body motion or providing physiological signalsthrough which body movement information may be derived. External bodymotion sensors include but are not limited to accelerometers,gyroscopes, magnetometers, resistive bend sensors, combinations thereof,and the like. Preferably, a combination using at least an accelerometerand gyroscope is used. Sensors through which body movement informationmay be derived include, but are not limited to, electromyogram (EMG),electrooculogram (EOG), electroencephalogram (EEG), electrocardiogram(EKG), or other physiological signals which can directly or indirectlymeasure movement metrics in the subject may be included if such sensorsand signals may be used to sense, detect, measure, and/or quantify thesubject's external body motion, or related aspects.

In embodiments where a gyroscope is a sensor of the present invention,the gyroscope functions on the principle of the Coriolis Effect and acapacitive-based sensing system. Rotation of the sensor causes a shiftin response of an oscillating silicon structure resulting in a change incapacitance. A typical application specific integrated circuit (ASIC),manufactured using a standard complementary metal oxide semiconductor(CMOS) manufacturing process, detects and transforms changes incapacitance into an analog output voltage, which is proportional toangular rate. The sensor element design utilizes differential capacitorsand symmetry to significantly reduce errors from acceleration andoff-axis rotations.

In embodiments where an accelerometer is a sensor of the presentinvention, it may optionally be a dual axis acceleration measurementsystem on a single monolithic integrated circuit (IC). Such embodimentsmay contain a polysilicon surface-micromachined sensor and signalconditioning circuitry to implement open-loop acceleration measurementarchitecture. For each axis an output circuit converts the analog signalto a duty cycle modulated (DCM) digital signal that can be decoded witha counter/timer port on a microprocessor. The dual axis accelerometer iscapable of measuring both positive and negative accelerations. Thesensor may be a surface micromachined polysilicon structure built on topof the silicon wafer. Polysilicon springs suspend the structure over thesurface of the wafer and provide a resistance against accelerationforces. Deflection of the structure is measured using a differentialcapacitor that consists of independent fixed plates and central platesattached to the moving mass. The fixed plates are driven by 180-degreeout of phase square waves. Acceleration will deflect the beam andunbalance the differential capacitor, resulting in an output square wavewhose amplitude is proportional to acceleration. Phase sensitivedemodulation techniques are then used to rectify the signal anddetermine the direction of the acceleration. The output of thedemodulator drives a duty cycle modulator (DCM) stage through a 32 kOhmresistor. At this point a pin is available on each channel to allow theuser to set the signal bandwidth of the device by adding a capacitor.This filtering improves measurement resolution and helps preventaliasing. After being low-pass filtered, the analog signal is convertedto a duty cycle modulated signal by the DCM stage. A single resistorsets the period for a complete cycle (T2). A 0 g acceleration produces anominally 50% duty cycle. The acceleration signal can be determined bymeasuring the length of the T1 and T2 pulses with a counter/timer orwith a polling loop using a low cost microcontroller.

In preferred embodiments, a single sensor unit comprising at least anaccelerometer and a gyroscope may be used. More preferably, a singlechip containing both a 3-axis accelerometer and a 3-axis gyroscope(e.g., Invensense MPU-6000), may be used. The sensor unit preferably notonly comprises at least an accelerometer and a gyroscope, but alsoallows for integration of other sensors external to the sensor unit.Preferably, the accelerometer and gyroscope are each three-axis sensorscapable of measuring their respective movements (acceleration andorientation) in each of the three dimensions of movement (X, Y and Z).Each of the accelerometer and gyroscope may output a separate signal fortheir respective measurements in each axis, and these signals are allconverted from analog to digital by a bank of analog-to-digitalconverters (ADC). The separate ADCs for each axis of the accelerometerand gyroscope allow for simultaneous sampling of each sensor andeliminate the need for an external multiplexer. Preferably the sensorunit as a whole, and the accelerometer and gyroscope in particular arecapable of operation with low power consumption. Preferably, theaccelerometer and gyroscope are user-programmable such that the user maydefine an operating range in which the sensors will work (e.g., theaccelerometer may be programmed to operate from as low as ±2 g to ashigh as ±16 g, and the gyroscope from as low as ±250 degrees/second toas high as ±2000 degrees/second). Some embodiments may include othersensors integrated into the sensor unit as well, for example, atemperature sensor, which may be used to monitor the temperature of thesensor unit and ensure it is operating properly and under safeconditions.

The sensor unit further preferably comprises a digital motion processor(DMP), which may perform some preprocessing or processing of the sensorsignals using motion-related algorithms. The digital motion processor atleast preprocesses and/or processes the accelerometer and gyroscopesignals to begin the analysis of the signals and to decrease theprocessing load on the external processor. Many embodiments may includeexternal or additional sensors that are not housed within the sensorunit, but whose signals are transmitted to the sensor unit forintegration with the accelerometer and gyroscope signals for furthertransmission to external components such as a processor. Such externalor additional sensors may include, but are not limited to, forcesensors, magnetometers, pressure sensors, bend sensors, combinationsthereof, and the like. These external or additional sensors communicatewith the sensor unit by means of an auxiliary communications interface.The digital motion processor can integrate the signal(s) from theseexternal or additional sensors along with the accelerometer andgyroscope signals and perform preprocessing or processing of all of thesignals together, thus further streamlining the data acquisition processand reducing the workload of the external processor (not shown).

In many embodiments, the movement disorder diagnostic device comprises akinetic sensor board (or subject worn external sensor). The kineticsensor board is preferably configured with at least an accelerometer anda gyroscope for quantifying the subject's motion. In some embodiments,the kinetic sensor board comprises at least three gyroscopes and threeorthogonal accelerometers, but in more preferable embodiments the threeof each sensor are replaced by at least one 3-axis accelerometer and atleast one 3-axis gyroscope. The kinetic sensor board also includes amicroprocessor and a power interface section.

In many embodiments, the electrical components of the movement disorderdiagnostic device further include a power receiver. The power receiveris the component, which receives the electrical charge from the externalpower source (not shown). The external power source can be any devicefor supplying power to the movement disorder diagnostic device. In someembodiments, the external power source may be a docking station to whichthe movement disorder diagnostic device can be connected, attached,docked, or placed into whereby a physical or proximal connection is madebetween the docking station and the movement disorder diagnostic devicethus allowing power to be transferred via the physical or proximalconnection. In other embodiments, the external power source may merelyinvolve plugging the movement disorder diagnostic device into atraditional power outlet. In still other embodiments, the external powersource may be an inductive charging mat or pad onto which the movementdisorder diagnostic device is placed and power may be inductivelytransferred between induction coils in the charging mat or pad and theinductive coils in the power receiver of the movement disorderdiagnostic device, as described herein. As the power receiver, which maybe wireless or wired depending on the embodiment, receives power, ittransfers said power to a power manager which controls and directs wherethe incoming power is delivered. If the movement disorder diagnosticdevice is not being presently used to measure a subject's body movementsand is instead being charged, then the power manager directs theincoming power to the device's battery for charging. It might bepossible and optional, though not necessarily preferred, for someembodiments to allow charging while the unit is being used to measure asubject's body motions, in which case the power manager would direct theincoming power to either the battery or to the micro-controller forpowering the device's operation for testing. However, it is morepreferable for the device, during operation for testing, to beuntethered and not in charging mode, and thus the battery would providepower to the unit for usage and testing purposes. The micro-controlleror microprocessor is the internal processing unit that directs the othercomponents to function. Thus, the micro-controller or microprocessordirects the power manager on where to direct the power it is receivingfrom either the power receiver or the battery. An electronic clockoperates as commonly known in the art to control synchronization andoperation of the device to maximize efficiency of power usage. The radioof the device controls and carries out communications between the devicecomponents, and between the movement disorder diagnostic device andexternal devices (not shown). The radio receives power directly from thepower manager. As described herein, the radio may be a Bluetooth®communications device to provide wireless communications with externalcomponents such as computers or processors, data acquisition circuitry,internet or cloud-based memory banks or databases, and the like, as wellas internal components such as the internal movement disorder diagnosticdevice memory, microprocessor, and the like. Both internal (betweenelectrical components of the subject-worn sensor device) and external(between the subject-worn sensor device and external components ordevices) communications may also be transmitted through wireless, wired,or a combination of both methods. The micro-controller comprisesalgorithms and protocols for coordinating the operation of at leastthese internal electrical components, and in some embodiments also forpreprocessing or processing sensor data.

The movement disorder diagnostic device of the present invention furtherpreferably comprises a transceiver module, or command module. Preferablythe sensor unit and transceiver/command module are enclosed in the samehousing constituting a single unit, though they may be separate units.The transceiver module includes communications electronics, such as aBluetooth® radio (e.g., BlueGiga WT12) to provide wirelesscommunications with the patient PC, on board memory, a microprocessor(e.g., Silicon Labs C8051F930), and a battery power supply (e.g., KokamLithium Power battery) that supplies power to both the transceivermodule and one or more sensor modules. The transceiver module may alsoinclude a USB port to provide battery recharging and serialcommunications with the patient PC. The transceiver module may alsoinclude a push button input.

In many embodiments, the transceiver/command module contains one or moreelectronic components such as a microprocessor for detecting both thesignals from the gyroscopes and accelerometers. Optionally, the one ormore electronic components also filter the kinetic motion signals, andmore preferably convert these signals, which are in an analog form intoa digital signal for transmission to a remote receiving unit, computeror other similar device. Though, more preferably, the device uses theherein described 3-axis accelerometer and 3-axis gyroscope chip whichcomprises ADC circuitry and thus outputs a digital signal. The one ormore electronic components are attached to the subject as part of themovement disorder diagnostic device. Further preferably, the one or moreelectronic components can receive a signal from the remote receivingunit or other remote transmitters. The one or more electronic componentsmay include circuitry for but are not limited to, for example, electrodeamplifiers, signal filters, analog to digital converter, Bluetooth®radio or other receiver, transmitter or transceiver components, a DCpower source and combinations thereof. The one or more electroniccomponents may comprise one processing chip, multiple chips, singlefunction components or combinations thereof, which can perform all ofthe necessary functions of detecting a kinetic or physiological signalfrom the electrode, storing that data to memory, uploading data to acomputer through a serial link, transmitting a signal corresponding to akinetic or physiological signal to a receiving unit and optionallyreceiving a signal from a remote transmitter. These one or moreelectronic components can be assembled on a printed circuit board or byany other devices or methods known to those skilled in the art includingbut not limited to an ASIC chip. Preferably, the one or more electroniccomponents can be assembled on a printed circuit board or by other meansso its imprint covers an area less than 4 in², more preferably less than2 in², even more preferably less than 1 in², still even more preferablyless than 0.5 in², and most preferably less than 0.25 in².

Preferably, the circuitry of the one or more electronic components isappropriately modified so as to function with any suitable miniature DCpower source. More preferably, the DC power source is a battery. Themost preferred battery of the present invention is lithium poweredbatteries. Lithium ion batteries offer high specific energy (the numberof given hours for a specific weight), which is preferable.Additionally, these commercially available batteries are readilyavailable and inexpensive. Other types of batteries include but are notlimited to primary and secondary batteries. Primary batteries are notrechargeable since the chemical reaction that produces the electricityis not reversible. Primary batteries include lithium primary batteries(e.g., lithium/thionyl chloride, lithium/manganese dioxide,lithium/carbon monofluoride, lithium/copper oxide, lithium/iodine,lithium/silver vanadium oxide and others), alkaline primary batteries,zinc-carbon, zinc chloride, magnesium/manganese dioxide,alkaline-manganese dioxide, mercuric oxide, silver oxide as well aszinc/air and others. Rechargeable (secondary) batteries includenickel-cadmium, nickel-zinc, nickel-metal hydride, rechargeablezinc/alkaline/manganese dioxide, lithium/polymer, lithium-ion andothers.

In some preferred embodiments, the system is capable of inductivecharging whereby an electromagnetic field is used to transfer energyfrom a charging mat or pad to the device. Preferably in suchembodiments, the charging mat or pad comprises and induction coil thatis used to create an alternating electromagnetic field. When the device,also comprising an induction coil, is placed on the charging mat or pad,the devices induction coil draws power from the electromagnetic fieldcreated by the charging mat's or pad's induction coil. The device's thenconverts this drawn power from electromagnetic field energy intoelectrical current and uses this electrical current to charge thedevice's battery.

Optionally, the data acquisition circuitry is designed with the goal ofreducing size, lowering (or filtering) the noise, increasing the DCoffset rejection and reducing the system's offset voltages. The dataacquisition circuitry may be constrained by the requirements forextremely high input impedance, very low noise and rejection of verylarge DC offset and common-mode voltages, while measuring a very smallsignal of interest. Additional constraints arise from the need for a“brick-wall” style input protection against ESD and EMI. The exactparameters of the design, such as input impedance, gain and passband,can be adjusted at the time of manufacture to suit a specificapplication via a table of component values to achieve a specificfull-scale range and passband.

Also optionally, a low-noise, lower power instrumentation amplifier isused. The inputs for this circuitry is guarded with preferably, externalESD/EMI protection, and very high-impedance passive filters to reject DCcommon-mode and normal-mode voltages. Still more preferably, theinstrumentation amplifier gain can be adjusted from unity toapproximately 100 to suit the requirements of a specific application. Ifadditional gain is required, it preferably is provided in a second-orderanti-bias filter, whose cutoff frequency can be adjusted to suit aspecific application, with due regard to the sampling rate. Still yetmore preferably, the reference input of the instrumentation amplifier istightly controlled by a DC cancellation integrator servo that usesclosed-loop control to cancel all DC offsets in the components in theanalog signal chain to within a few analog-to digital converter (ADC)counts of perfection, to ensure long term stability of the zeroreference.

Further optionally, where analog signals are acquired, such signals areconverted to a digital form. This can be achieved with an electroniccomponent or processing chip through the use of an ADC. More preferably,the ADC restricts resolution to 16-bits due to the ambient noiseenvironment in such chips. Despite this constraint, the ADC remains thepreferable method of choice for size-constrained applications such aswith the present invention unless a custom data acquisition chip is usedbecause the integration reduces the total chip count and significantlyreduces the number of interconnects required on the printed circuitboard.

Preferably, the circuitry of the sensor board comprises a digitalsection. More preferably, the heart of the digital section of the sensorboard is a micro-controller or processor. The microcontroller orprocessor preferably contains sufficient data and program memory, aswell as peripherals which allow the entire digital section to be neatlybundled into a single carefully programmed processing chip. Still morepreferably, the onboard counter/timer sections are used to produce thedata acquisition timer.

Preferably, the circuitry for the one or more electronic components isdesigned to provide for communication with external quality control testequipment prior to sale, and more preferably with automated final testequipment. In order to supply such capability without impacting thefinal size of the finished unit, one embodiment is to design acommunications interface on a separate printed circuit board (PCB) usingthe SPI bus with an external UART and level-conversion circuitry toimplement a standard serial interface for connection to a personalcomputer or some other form of test equipment. The physical connectionto such a device requires significant PCB area, so preferably thephysical connection is designed to keep the PCB at minimal imprint area.Optionally, the physical connection is designed with a break-off tabwith fingers that mate with an edge connector. This allows all requiredfinal testing and calibration, including the programming of theprocessing chip memory, can be carried out through this connector, withtest signals being applied to the analog inputs through the normalconnections which remain accessible in the final unit. By using edgefingers on the production unit, and an edge connector in the productiontesting and calibration adapter, the system can be tested and calibratedwithout leaving any unnecessary electronic components or too large a PCBimprint area on the final unit. More preferably, no break-off tabs arerequired where a pogo-pin test pad design is used allowing the PCB to betested without breaking apart.

Preferably, the circuitry for the one or more electronic componentscomprises nonvolatile, rewriteable memory for storing kinematic data, aswell as RAM used to store operational data such as the pending mode(i.e., sleep or test mode), period and number of seconds to record data,daily alarm time, amount of time to collect data, and the like.Preferably, enough nonvolatile memory is included to record at least 8hours of kinematic data, though preferably more. Alternatively, if thecircuitry for the one or more electronic components doesn't comprisenonvolatile, rewriteable memory then an approach should be used to allowfor reprogramming of the final parameters such as radio channelizationand data acquisition and scaling. Without nonvolatile, rewriteablememory, the program memory can be programmed only once. Therefore oneembodiment of the present invention involves selective programming of aspecific area of the program memory without programming the entirememory in one operation. Preferably, this is accomplished by settingaside a specific area of program memory large enough to store severalcopies of the required parameters. Procedurally, this is accomplished byinitially programming the circuitry for the one or more electroniccomponents with default parameters appropriate for the testing andcalibration. When the final parameters have been determined, the nextarea is programmed with these parameters. If the final testing andcalibration reveals problems, or some other need arises to change thevalues, additional variations of the parameters may be programmed. Thefirmware of various embodiments of the present invention scans for thefirst blank configuration block and then uses the value from thepreceding block as the operational parameters. This arrangement allowsfor reprogramming of the parameters up to several dozen times, with nosize penalty for external EEPROM or other nonvolatile RAM. The circuitryfor the one or more electronic components has provisions for in-circuitprogramming and verification of the program memory, and this issupported by the breakoff test connector, as well as the pop-pin testpad. The operational parameters can thus be changed up until the time atwhich the test connector is broken off just before shipping the finalunit. Thus the manufacturability and size of the circuitry for the oneor more electronic components is optimized. Most preferably, however,the system is designed to allow for over-the-air programming even oncethe circuit design has been completed and the circuit has been installedinto the movement disorder diagnostic device. In such embodiments, thefirmware contains a boot-loading program that, once turned on, looks forprogramming signals. Thus, such programming signals can be delivered andthe device updated, even after manufacture and shipment to a clinic, oreven when in the possession of a subject.

Preferably the circuitry of the one or more electronic componentsincludes an RF transmitter and/or an RF receiver, or a RF transceiver.Still more preferably the circuitry of the one or more electroniccomponents includes a Bluetooth® radio system requiring an average ofabout 42 mA of electrical current to operate. Another feature of thecircuitry of the one or more electronic components preferably is anantenna. The antenna, preferably, is integrated in the rest of thecircuitry. The antenna can be configured in a number of ways, forexample as a single loop, dipole, dipole with termination impedance,logarithmic-periodic, dielectric, or strip conduction or reflectorantenna. The antenna is designed to include but not be limited to thebest combination of usable range, production efficiency and end-systemusability. Preferably, the antenna consists of one or more conductivewires or strips, which are arranged in a pattern to maximize surfacearea. The large surface area will allow for lower transmission outputsfor the data transmission. The large surface area will also be helpfulin receiving high frequency energy from an external power source forstorage. Optionally, the radio transmissions of the present inventionmay use frequency-selective antennas for separating the transmission andreceiving bands, if a RF transmitter and receiver are used on theelectrode patch, and polarization-sensitive antennas in connection withdirectional transmission. Polarization-sensitive antennas consist of,for example, thin metal strips arranged in parallel on an insulatingcarrier material. Such a structure is insensitive to or permeable toelectromagnetic waves with vertical polarization; waves with parallelpolarization are reflected or absorbed depending on the design. It ispossible to obtain in this way, for example good cross polarizationdecoupling in connection with linear polarization. It is furtherpossible to integrate the antenna into the frame of a processing chip orinto one or more of the other electronic components, whereby the antennais preferably realized by means of thin film technology. The antenna canserve to just transfer data or for both transferring data to and forreceiving control data received from a computer device and/or receivingunit which can include but is not limited to a wireless relay, acomputer or a processor system. Optionally, the antenna can also serveto receive high-frequency energy (for energy supply or supplement). Inany scenario, only one antenna is required for transmitting data,receiving data and optionally receiving energy. Optionally, directionalcouples can be arranged on the transmitter outputs of the electrodepatch and/or the computer device and/or receiving unit. The couplersbeing used to measure the radiated or reflected radio wave transmissionoutput. Any damage to the antenna (or also any faulty adaptation) thuscan be registered, because it is expressed by increased reflectionvalues.

An additional feature of the present invention is an optionalidentification unit. By allocating identification codes—a patient code,the computer device and/or receiving unit is capable of receiving andtransmitting data to several subjects, and for evaluating the data ifthe computer device and/or receiving unit is capable of doing so. Thisis realized in a way such that the identification unit has controllogic, as well as a memory for storing the identification codes. Theidentification unit is preferably programmed by radio transmission ofthe control characters and of the respective identification code fromthe programming unit of the computer device and/or receiving unit to thepatient worn unit. More preferably, the unit comprises switches asprogramming lockouts, particularly for preventing unintentionalreprogramming.

In any RF link, errors are an unfortunate and unavoidable problem.Analog systems can often tolerate a certain level of error. Digitalsystems, however, while being inherently much more resistant to errors,also suffer a much greater impact when errors occur. Thus the presentinvention, when used as a digital system, preferably includes errorcontrol sub architecture. Preferably, the RF link of the presentinvention is digital. RF links can be one-way or two-way. One-way linksare used to just transmit data. Two-way links are used for both sendingand receiving data.

If the RF link is one-way error control, then this is preferablyaccomplished at two distinct levels, above and beyond the effort toestablish a reliable radio link to minimize errors from the beginning.At the first level, there is the redundancy in the transmitted data.This redundancy is performed by adding extra data that can be used atthe computer device and/or receiving unit or at some station to detectand correct any errors that occurred during transit across the airwaves.This mechanism known as Forward Error Correction (FEC) because theerrors are corrected actively as the signal continues forward throughthe chain, rather than by going back to the transmitter and asking forretransmission. FEC systems include but are not limited to Hamming Code,Reed-Solomon and Golay codes. Preferably, a Hamming Code scheme is used.While the Hamming Code scheme is sometimes maligned as being outdatedand underpowered, the implementation in certain embodiments of thepresent invention provides considerable robustness and extremely lowcomputation and power burden for the error correction mechanism. FECalone is sufficient to ensure that the vast majority of the data istransferred correctly across the radio link. Certain parts of the packetmust be received correctly for the receiver to even begin accepting thepacket, and the error correction mechanism in the computer device and/orreceiving unit reports various signal quality parameters including thenumber of bit errors which are being corrected, so suspicious datapackets can be readily identified and removed from the data stream.

Preferably, at a second, optional level, an additional line of defenseis provided by residual error detection through the use of a cyclicredundancy check (CRC). The algorithm for this error detection issimilar to that used for many years in disk drives, tape drives, andeven deep-space communications, and is implemented by highly optimizedfirmware within the electrode patch processing circuitry. Duringtransmission, the CRC is first applied to a data packet, and then theFEC data is added covering the data packet and CRC as well. Duringreception, the FEC data is first used to apply corrections to the dataand/or CRC as needed, and the CRC is checked against the message. If noerrors occurred, or the FEC mechanism was able to properly correct sucherrors as did occur, the CRC will check correctly against the messageand the data will be accepted. If the data contains residual errors(which can only occur if the FEC mechanism was overwhelmed by the numberof errors), the CRC will not match the packet and the data will berejected. Because the radio link in this implementation is strictlyone-way, rejected data is simply lost and there is no possibility ofretransmission.

More preferably, the RF link utilizes a two-way (bi-directional) datatransmission. By using a two-way data transmission the data safety issignificantly increased. By transmitting redundant information in thedata emitted by the electrodes, the computer device and/or receivingunit is capable of recognizing errors and request a renewed transmissionof the data. In the presence of excessive transmission problems such as,for example transmission over excessively great distances, or due toobstacles absorbing the signals, the computer device and/or receivingunit is capable of controlling the data transmission, or to manipulateon its own the data. With control of data transmission it is alsopossible to control or re-set the parameters of the system, e.g.,changing the transmission channel. This would be applicable for exampleif the signal transmitted is superimposed by other sources ofinterference then by changing the channel the computer device and/orreceiving unit could secure a flawless and interference freetransmission. Another example would be if the signal transmitted is tooweak, the computer device and/or receiving unit can transmit a commandto increase its transmitting power. Still another example would be thecomputer device and/or receiving unit to change the data format for thetransmission, e.g., in order to increase the redundant information inthe data flow. Increased redundancy allows transmission errors to bedetected and corrected more easily. In this way, safe data transmissionsare possible even with the poorest transmission qualities. Thistechnique opens in a simple way the possibility of reducing thetransmission power requirements. This also reduces the energyrequirements, thereby providing longer battery life. Another advantageof a two-way, bi-directional digital data transmission lays in thepossibility of transmitting test codes in order to filter out externalinterferences such as, for example, refraction or scatter from thetransmission current. In this way, it is possible to reconstruct falselytransmitted data.

The computer device and/or receiving unit of various embodiments of thepresent invention may be any device known to receive RF transmissionsused by those skilled in the art to receive transmissions of data. Thecomputer device and/or receiving unit, by way of example but notlimitation, can include a communications device for relaying thetransmission, a communications device for re-processing thetransmission, a communications device for re-processing the transmissionthen relaying it to another computer device and/or receiving unit, acomputer with wireless capabilities, a PDA with wireless capabilities, aprocessor, a processor with display capabilities, a desktop computer,laptop computer, tablet computer, smart phone, and combinations of theseor like devices known or developed hereafter. Optionally, the computerdevice and/or receiving unit can further transmit data both to anotherdevice and/or back. Further optionally, two different computer devicesand/or receiving units can be used, one for receiving transmitted dataand another for sending data. For example, with the movement disorderdiagnostic system of the present invention, the computer device and/orreceiving unit of the present invention can be a wireless router, whichestablishes a broadband Internet connection and transmits thephysiological signal to a remote Internet site for analysis, preferablyby the subject's physician. Another example is where the computer deviceand/or receiving unit is a PDA, computer, tablet or cell phone, whichreceives the physiological data transmission, optionally re-processesthe information, and re-transmits the information via cell towers, landphone lines or cable to a remote site for analysis. Another example iswhere the computer device and/or receiving unit is a computer orprocessor, which receives the data transmission and displays the data orrecords it on some recording medium, which can be displayed ortransferred for analysis at a later time.

The digitized kinetic or physiological signal is then transmittedwirelessly to a computer device and/or receiving unit. This computerdevice and/or receiving unit allows the subject wide movement.Preferably, the computer device and/or receiving unit can pick up andtransmit signals from distances of greater than about 5 feet from thesubject, more preferably greater than about 10 feet from the subject,even more preferably greater than about 20 feet from the subject, stilleven more preferably greater than about 50 feet from the subject, stilleven more preferably greater than about 200 feet from the subject, andmost preferably greater than about 500 feet from the subject. Thecomputer device and/or receiving unit is used to re-transmit the signalbased in part from the movement or physiological signal from themovement disorder diagnostic device wirelessly or via the internet toanother monitor, computer or processor system. This allows the clinicianor monitoring service to review the subject's movement or physiologicalsignals and if necessary to make a determination, which could includemodifying the patients treatment protocols.

Optionally, the system of the present invention includes some form ofinstruction, which can be in written form on paper or on a computermonitor, on a video, or communicated via teleconference orvideoconference between the subject and clinician, physician ortechnician. Optionally, a video is used which instructs the subjects toperform a series of tasks during which their kinetic motion and/or EMGand/or other physiological signals related to their motion can bemeasured. Since the system of the present invention is preferably usedin the subject's home, a video giving directions and/or describingvarious tasks to be performed by the subject is included with thesystem. The video may be accessed or viewed for example but not by wayof limitation through use of video tape, DVD, podcast as part ofcomputer software provided, through the internet, or the like. Thedirections could include but are not limited to instructions on how todon the device, how to turn the device on, and the like. The descriptionof various tasks could include but is not limited to exercises which aretypically used by a technician, clinician or physician to evaluate asubject with a movement disorder including but not limited to handgrasps, finger tapping exercises, other movements and the like. Oneembodiment of a video includes the technician, clinician or physicianlooking into the camera, as they would a patient, and instructing themon device setup, instructing the patients through each of the tasks tobe performed, providing verbal encouragement via video after a task, andasking subject's to repeat a task if it was not completed. Preferably,these video clips are edited and converted to MPEG or other similar filetypes either automatically or using editing software. For movementdisorders such as Parkinson's disease preferably the technician,clinician or physician instructs the user through multiple tasks as perthe UPDRS, tremor rating scale (TRS), or similar scale guidelinesincluding tasks, movements, motions, activities, and the like designedor intended to analyze symptoms of movement disorders including, but notlimited to, rest tremor, postural tremor, and action tremor,bradykinesia, rigidity, gait, dyskinesia, and the like. More preferably,if the video is linked to the user interface software, the software willautomatically detect if a subject has performed the requested task andprovide feedback through the video to either repeat the task or continueto the next task. Still more preferably, once the user has setup thedevice, it will continually record the subject's movement data(including before and after any directed video tasks), be able toquantify the severity of the subject's symptoms during activities ofdaily living, and communicate that information with the clinician andsubject through interface software, video, or the like.

Also optionally, the subject may not be required or instructed toperform a specific task or group of tasks, but instead measurement andquantification of the subject's symptom(s) and side effect(s) may becarried out while the subject wears the diagnostic device duringactivities of daily living, or simply on a continuous basis. In otherwords, the subject may wear the diagnostic device while cleaning his orher home, doing yard work, cooking, exercising, dancing, or othersimilar activities that are normally performed naturally during thecourse of one's day. In such embodiments, measurements may be takenperiodically according to a predetermined interval or start time, may beinitiated by the subject based on the activity he or she is performingor is about to perform, may be initiated by the clinician, physician ortechnician either in-clinic or remotely, or the system may detect achange in activity or the onset of a symptom or side effect and mayautomatically perform the measurement, quantification and subsequentsteps in order to adjust the therapy device automatically. Where theclinician, physician or technician initiates the process remotely, he orshe may interrogate the system via electronic communication means andbegin the process.

In many embodiments, an additional step of identifying or determiningthe activity, movement or motion the subject is performing may need tobe determined. As noted, the subject may input a desired activity,movement or motion into the device to begin the assessment andadjustment. In other embodiments, the diagnostic device may detect achange in the subject's activity, movement or motion, or perhaps theonset of a symptom or side effect, and automatically begin the processto adjust the therapy parameters. By way of non-limiting example, if asubject who is wearing the diagnostic device is at work, performinglittle physical activity, movement or motion, and then leaves work todrive home or exercise at lunch, the system may automatically detect andidentify or determine the increased level of activity, movement ormotion and also automatically initiate the process of adjusting thetherapy parameters to provide better therapy levels allowing the subjectto perform the newly altered activity, movement or motion more properly,comfortably and safely. Similarly, if the subject begins to exhibit achange in symptoms or side effects, for example the onset of a tremor,the system may detect and identify or determine the symptom or sideeffect and automatically initiate the process to adjust or tune theparameters or settings to counteract the symptom or side effect andreturn the subject to the most normal functionality as possible.

The present invention includes various methods of measuring and scoringthe severity of a subject's movement disorder. These methods include anumber of steps which may include but are not limited to measuring asubject's external body motion; transmitting wirelessly a signal basedin part on the subject's measured external body motion; receiving thewirelessly transmitted signal; downloading data from memory; and scoringthe severity of a subject's movement disorder based in part on thewirelessly transmitted or downloaded signal. Optionally, anelectromyogram of the subject's muscle activity and/or otherphysiological signals may be obtained and used in part to score theseverity of the subject's movement disorder.

Several preferred embodiments of the present invention include a trainedscoring algorithm to determine and provide objective scoring frommovement data acquired by the movement disorder diagnostic device. Thetrained scoring algorithm in part comprises a mathematical model orquantitative representation, used to process kinematic features computedfrom the movement data and may include some of those steps known tothose skilled in the art. In some embodiments of the present invention,the scoring may done on a continuously variable scale of 0-4 with scoressubstantially similar to or predictive of scores that would be given onthe Unified Parkinson's Disease Ratings Scale (UPDRS) by an expertclinician. (“Expert clinician” for the purposes of this application istaken to mean a doctor, nurse, researcher, or other medical orscientific professional trained for and sufficiently experienced in thetask of interest, e.g., motor function assessment using the UPDRS, orDBS programming.)

The present invention also preferably includes DBS parameter controlmethods and tuning algorithms for determining and setting the DBSparameters used to deliver DBS therapy to the subject. In manyembodiments, the parameter control methods and algorithms utilize asystem of tuning maps, or other parameter display or visualizationmethods or tools, for DBS programming. Although the term ‘tuning map’ isused throughout this application, it is intended that tuning mapsinclude any such method or tools that may be used for displaying therapyparameters or settings for human review and/or analysis. As notedherein, in the present invention, the tuning maps are preferably onlyutilized for optional clinician, physician or technician review of thesecond levels or optimized levels of therapy parameters or settings. Thetuning maps utilized by the present invention are a tool used forrecording DBS parameters, the subject's response to stimulation at thoseparameters, and allowing a clinician, physician or technician tooptionally or periodically review parameters and settings. Preferably,when utilized, the tuning map is a two-dimensional representation of athree-dimensional graph or display of data.

The subject is preferably first screened and determined to be a viablecandidate for DBS therapy, and then has at least one DBS lead surgicallyimplanted into his or her brain. The screening process preferablyinvolves providing the subject with a diagnostic device for monitoringand assessing the subject's movement disorder systems. Generally, a DBStherapy system will include one or more implanted leads with each leadhaving one or more electrodes. These leads are connected to a pulsegenerator, which generally is also implanted with the leads. The pulsegenerator can be implanted in the cranium or preferably in many caseswiring from the leads will be threaded down the subject's neck and thepulse generator will be implanted or embedded in the subject's upperchest or abdomen. The pulse generator will run on a battery, which canin some cases recharged through techniques such as inductive coupling.The DBS therapy system can be adjusted generally through communicationbetween a programming module or unit and the impulse generator. Such asystem, as an example, is described in U.S. patent application Ser. No.12/818,819, filed on Jun. 18, 2010, and Ser. No. 15/210,990, filed onJul. 15, 2016, which are hereby incorporated by reference. Other systemsas known or later developed in the art can also be adjusted with thedevices, method and systems of the present invention. Thus, because ofthe highly invasive nature of therapies such as DBS, requiring surgicalimplantation of the therapy device, the present invention alsooptionally provides the screening capabilities to ensure the subjectwould benefit from such a therapy before undergoing the costly andonerous surgical procedure

The subject may utilize this device at home and during other normal lifeactivities as well, or in a clinical setting, and during the performanceof motor and cognitive tests, and while taking his or her prescribedmedications for treatment and management of the movement disordersymptoms. The device monitors and records the occurrence of thesesymptoms and then analyzes the data by means of algorithm(s) designed toaccount for the multitude of variables including demographic information(age, gender, weight, blood pressure, physical activity, medication use,disease duration, Hoehn & Yahr, marital status/caregiver support,patient expectations, and the like), the type of anticipated DBS therapy(DBS target, unilateral/bilateral implant, constant current versusconstant voltage, and the like), non-motor response (UPDRS parts I andII scores, cognition and quality of life assessments, neuropsychologytests, and the like), motor response (UPDRS parts III and IV scores),sensor recordings of symptom occurrence and severity, response tomedication, and the like. Generally, subjects who respond favorably totypical medications tend to respond well to DBS therapy. The algorithmanalyzes all of the data and makes a determination as to whether thepatient is likely to be a good candidate for DBS therapy. The algorithmmay optionally employ any one, or a combination of, statistical modelscurrently known to those in the art, including, but not limited tolinear and non-linear classification methods such as logisticregression, artificial neural networks, k-means clustering, and thelike. The algorithm may output the determination in different ways. Inother embodiments, the algorithm may provide a percent likelihood offavorable DBS outcomes for the subject. Still other embodiments maypresent the multitude of data described above in a chart or graph formatin order to allow a clinician, physician or technician to review thedata and results and confirm or deny that the subject would benefit fromsuch therapy. By way of non-limiting example, various embodiment mayemploy a visual display that depicts a pie chart wherein the pie chartis populated showing the measured and quantified occurrences of asymptom(s) such as tremor throughout the day. Any other method known tothose skilled in the art for displaying the test results and optionallythe input data, or combinations of both, can be envisioned forpresenting the data to a clinician, physician or technician for optionalreview of the screening viability determination. Additionally, thealgorithm may provide suggested DBS lead placements in the subject'sbrain based at least in part on the symptoms and side effects thesubject experiences, their severity, and the like. If the subject isdetermined to be a favorable candidate, the clinician then initiates theprocess for DBS therapy, which begins with the surgical implantation ofat least one DB S lead into the subject's brain. The main purpose of thescreening process is to provide a pre-surgical indication of whether thesubject would benefit from DBS therapy. This minimizes the likelihood ofneedless surgery and risk for the subject, as well as time, cost, andresources utilized.

For initial DBS tuning, it may be preferable to perform a monopolarreview, which is using a single DBS contact in the monopolarconfiguration. However, bipolar, or greater, review may be accomplishedas well with the present invention. A single DBS lead has severalcontact points, or electrodes, which can be used to administer theelectrical stimulation. Preferably, in many embodiments of the presentinvention, the DBS leads comprise a plurality of dual-mode contactswhich are able to both transmit signals from the lead into the subject'sbrain, and to detect, acquire or measure signals from the subject'sbrain (e.g., electrical or electrophysiological signals). A DBS lead mayhave at least one ground contact, and at least 3 battery contacts fordelivering the electrical stimulation, though fewer or more batterycontacts may be included. Once the lead, or leads, is implanted into thesubject's brain, the subject then undergoes an initial programmingsession. During the initial programming session, a clinician enters aset of initial test variables (as described above), and administers theelectrical impulse to the subject's brain. Typically, the initial testparameters are set and fixed, and then in later iterations the amplitude(voltage or current), as well as other variables are gradually increasedor otherwise changed. The results of the impulse may be recorded in atuning map for optional review indicating the effect which the given setof parameters had on the subject's symptoms, feelings, and the like, andare simultaneously communicated to the tuning algorithm(s). The subjectis generally awake for the programming sessions and gives feedback tothe clinician regarding any sensations or effects that the subjectexperiences. The results may include any sort of measured, observed, orcalculated response, or combinations thereof including, but not limitedto, sensor recordings (for quantifying symptoms as described above),patient responses and perceptions, clinician observations, and clinicianscores (e.g., UPDRS, MDS-UPDRS, and the like). In some embodiments, itis possible that the tuning process may be entirely automated such thatthe tuning map is populated entirely by, and/or the algorithm(s) issupplied with sensor recordings and/or measured and quantified motorsymptom data of the subject's response to the DBS therapy and no humanobservation or calculation is required. Based on the results of theinitial test parameters, the tuning map is populated, and the tuningalgorithm(s) changes the parameters to more effectively address thesubject's symptoms, and the process is repeated. Preferably, in suchembodiments, the tuning map is populated simultaneously with supplyingthe measurements to the algorithm(s), and the tuning map remains ahidden or dormant feature that can optionally be accessed for review ofthe parameters and settings. Typically, the end result of the tuningprocess is to optimize the effectiveness of the therapy (i.e., decreasethe severity and occurrence of symptoms as much as possible) whileminimizing the volume of activated brain tissue, but the particulargoals and needs of the subject will dictate exactly what the desiredresult is for each subject.

Many embodiments of the present invention employ an intelligent systemprogramming capability that greatly decreases the amount of clinician“guess-work” involved in selecting the iterations of DBS parametervalues by providing an expert system that efficiently determinesappropriate DBS settings. Similar to above, for the first postoperativeprogramming session, the system performs an automated monopolar survey.The subject may wear a motion sensor unit comprising sensors formeasuring movement, and performs motor assessments at various DBSsettings. Stimulation is incrementally increased from zero at eachcontact until symptoms stop improving as measured by the motion sensorunit, perceptions, clinician observations or scores, or the like, oruntil side effects appear as measured by the motion sensor unit, theclinician, or the patient. In many embodiments, adjustments may be basedon current rather than voltage since the functional response may berelated to the amount of current delivered to a specific target. Forconstant current IPGs, the current amplitude will be set directly andfor constant voltage IPGs, the voltage amplitude may be set based on therequired current and impedance measured on the electrode. Preferably,the system is capable of operating in either constant current orconstant voltage modes, depending on the clinician's preference and theneeds of the particular subject. The monopolar survey helps determinethe functional anatomy around the DBS lead site and narrows the searchspace for determining an optimal set of programming parameters. Atherapeutic window will be defined as the region in which a patientexhibits optimal symptomatic benefits without side effects. Thistherapeutic window will be valuable at the initial postoperativeprogramming session as well as all future adjustment sessions fordetermining the current amplitude when side effects begin to occur oneach contact. This therapeutic window is then used to define a sideeffect region. The system includes internal electric field modeling todetermine how this side effect region can be avoided, possibly byshaping the electric field with a bi- or tripolar configuration oraltering the pulse width. Bipolar or tripolar configuration refers tothe simultaneous delivery of electrical impulses from two or three,respectively, contacts on the DBS lead to shape the electrical fielddelivered to the subject's brain. For monopolar stimulation, currentfalls off proportionally to the distance from the negative electrodecontact. For bipolar stimulation, current decreases proportional to thesquare of the distance to the negative contact, but increases by thesquare of the distance between the negative and positive contacts.Efficient stimulation algorithms are used to find a set of parametersthat optimize for efficacy while minimizing side effects and batteryusage. The patient and/or clinician will be able to give higher weightto a given item, parameter, or symptom (e.g., tremor severity) that maybe most important to him or her. Many clinicians are ignorant of thebattery voltage of the IPG battery and therefore unaware that a slightincrease of the stimulation amplitude above the battery voltage willactivate voltage doubler or tripler circuits in the IPG, significantlyincreasing battery drain and shortening battery life by half. Thealgorithms will automatically avoid increasing voltage above the batteryvoltage unless necessary for finding a therapeutic window. After theautomated monopolar survey is completed and a patient-specificfunctional map is developed during the initial postoperative programmingvisit, subsequent programming adjustments will be much simpler andfaster.

Basing an optional and one of the preferable algorithm(s) on functional,rather than on structural, anatomy has several advantages. First, mostDBS programmers are not imaging experts and may not have the wherewithalto correctly interpret complex anatomies. More importantly, thetherapeutic mechanisms of DBS are largely unknown. The optimalstimulation location differs across patients and is based on functionalrather than structural anatomy. Therefore, the system will beindividualized to each subject's response and be far superior torecently developed DBS programming aids, which rely on anatomicalassumptions, imaging, and statistical modeling to estimate the electricfield at various anatomical targets.

The intelligent system programming capability takes the results of theinitial test parameters and automatically populates the tuning map whilesimultaneously providing these results to an algorithm(s). The system'stuning algorithm(s) analyze these results and provide the next iterationof DBS parameters. These provided parameters or settings may be reviewedand possibly edited by the clinician, physician or technician, or may beautomatically entered into the subject's therapy device thus programmingthe therapy device to operate according to those settings. Effectively,the system provides optimized DBS parameters or settings which eitherare automatically implemented, or may act as a guide for the clinicianin setting the IPG for the next iteration of testing (particularly forthe initial programming session). This reduces the clinician's need toperform the analysis and determine which parameters to change and howmuch to change them. The clinician may have the option to edit or electany one or combination of the system's suggested parameters for the nextiteration. This intelligent programming system may be performedin-clinic during a traditional programming appointment, whereby thesystem provides the suggested DBS parameters or settings to theclinician and the clinician can review and edit the parameters orsettings through the software which in turn adjusts the settings andparameters on the IPG. Alternatively, the intelligent programming maytake place remotely whereby the system automatically and intelligentlyprovides optimized parameters or settings and programs them into thesubject's therapy device, or communicates any data and suggested DBSparameter settings to the clinician, physician or technician who islocated some distance away while the subject remains at home, and theclinician then reviews and elects to approve or edit the suggestedsettings, which are sent to the IPG to update the parameters of the DBSadministered to the subject, or still further the clinician may instructthe diagnostic device to perform another iteration of testing, ratherthan editing the suggested parameters or settings herself. Where theclinician, physician or technician does perform the option or periodicreview, the data (e.g., parameters and settings, test results, and thelike) may be displayed for his or her review in a tuning map asdescribed. Because the clinician is not required to be physicallypresent at the time of programming, the system instead may rely onsystem and user reports, which are sent to the clinician. These reportsmay be made by the system sending reports to the clinician, video and/oraudio conferences between the subject and the clinician, the subjectkeeping a medication diary to report medication schedules and symptomoccurrence and severity, transmitted tuning maps, and the like.

Some embodiments of the present invention provide the clinician,physician or technician the ability to manually make the determinationas to what therapy parameters to use with the subject's therapy devicebased in part on the tuning map or data corresponding to the subject'smeasured and quantified motor symptoms or based on other data measuredby the movement disorder diagnostic device from the subject. Again, thisis solely an optional review designed for periodic analysis of thealgorithm(s)′ function and to ensure that the subject's needs are beingmet adequately and safely. The present invention further optionallyallows the clinician, physician or technician the ability to reviewrecommended second level therapy parameters before or after thosetherapy parameters or settings are entered into the therapy device andto change those recommended settings.

The present invention includes intelligent remote programming methodsand algorithms utilizing a database, which may be cloud-based in someembodiments, allowing for remote DBS adjustments being possible withoutthe subject even leaving his or her home, and in some intelligentembodiments without clinician involvement. The system may provideautomated, objective scoring and tuning algorithms to take theprogramming expertise out of the hands of a clinician and perform itremotely, and enable high-quality programming to all DBS recipients,regardless of proximity to or availability of expert programmers.Ideally, the subject would not have to travel to the clinic or facilityfor programming unless a problem was detected requiring personal medicalcare. Such embodiments necessarily include the integrated systemprogramming capability whereby the software directly communicates withthe hardware to set the DBS parameters according to the values enteredinto the software in order to enable the periodic or optional review bythe clinician, physician or technician. For such optional or periodicreview, rather than in-clinic programming sessions, the software wouldcommunicate with the DBS hardware, which is located remotely, implantedinto the subject. In these embodiments, the implanted device may performan intelligent system analysis, creating a suggested set of DBSparameters for the particular subject, and then securely communicate allthe data and suggested parameters to a centralized or cloud-baseddatabase, which analyzes all the information and then sends programmingcommands to the subject's IPG to change the DBS settings. This databaseand intelligent remote system allows for continued or repeated DBStuning without requiring the patient to travel to a clinician, andwithout requiring a clinician to spend the time analyzing subject data.The benefits of such a system go beyond the convenience of minimizingtravel time and access to clinicians and include the ability to deliversuch reports at virtually any time (the subject and clinician are nottied to a particular appointment time and window, and the clinician canreview any data at any time if desired), continuous and repeatedmonitoring of the subject's and system's statuses, and delayedmonitoring whereby results of changed parameters can be monitored later,which is particularly useful for symptoms that may not react to changesrapidly (i.e., during the normal clinical appointment time period).

Further, the system preferably includes the capability to performhardware diagnostic tests remotely of any and all of the individualunits or modules used with the present invention, including thesubject's therapy device (e.g., implanted pulse generator), movementdisorder diagnostic device, programmer unit, and the like. The hardwarein such embodiments is able to monitor and/or periodically interrogatethe system to detect changes in system conditions such as batterystatus, electrode impedance, and the like. The system then sends theresults of these diagnostic tests back to the clinician who can monitorthem to determine if a problem arises requiring the subject to return tothe clinic for adjustments, repairs, or other such purposes. Furtherstill, such embodiments using remote programming and control may includemedication delivery systems as well. Such delivery systems include adrug reservoir for holding and storing medication, and infusion pump fordelivering said medication from the reservoir to the subject. Suchembodiments may determine based on recorded signals that the subject'ssymptoms are particularly severe or occurring more frequently.

Some embodiments may optionally include a closed-loop or semi-closedloop drug titration system. In such embodiments, when the subject'sprescribed medication is initially taken or delivered, the system thenmonitors the subject's symptoms. The system continues to monitor thesymptoms until and after it detects that the subject's symptomsincrease, maintain, or only very slightly decrease in severity and rateof occurrence. In a semi-closed loop system, a report, warning, alert,or some other signal would then be sent to the subject or to thesubject's clinician. In such case, the subject could take moremedication, or the clinician could send a command for an integrated drugdelivery pump to administer another dose. In a close-loop system, upondetection of the above indicators, the system would automaticallyadminister an additional dose of medication through an integratedmedication delivery pump. In either case, the system is capable ofsubstantially continuous symptom monitoring to determine when thesubject is experiencing an increase in symptom activity, ineffectivemedication delivery, or a wearing off of medication in order toadminister additional medication to control the subject's symptoms.Further, such embodiments must also be able to monitor and detect theoccurrence of side effects arising from the medication, and to stopadministering medication when such side effects begin to manifest.

It will be further noted that use of the device and method of thepresent invention in combination with treatment directed at stopping orslowing the progression or onset of a movement disorder is intended tooptionally include the use of the movement disorder monitoring devicewith a broad scope of pharmaceutical agents and/or other treatmentsdirected at stopping or slowing the progression or onset of a movementdisorder. Neuroprotective drugs provide one specific example of acompound that can be used to stop or slow the progression or onset of amovement disorder. Briefly stated, neuroprotective drugs include a broadset of compounds that serve to eliminate or reduce neuronal death in thecentral and/or peripheral nervous systems, hence eliminating certainmovement disorder symptoms that can follow neuronal death and stoppingprogression or onset of a movement disorder disease. By way of specificexample, in the case of PD certain drugs have been and are beingexamined and may be found to be effective at eliminating or reducingdeath of a subject's dopamine producing neurons, and the efficacy ofsuch drugs over extended periods of time could be objectively monitoredusing the device and method of the present invention as a means tocollect and review movement disorder symptom data over extended periodsof time. By way of example, neuroprotective drugs that have been and arebeing examined for their potential in stopping or slowing theprogression of movement disorders such as PD include drugs such asselegiline, riluzole and lazabemide. It is to be understood that thescope of the present invention is intended to cover the use, with thedevice and as part of the method of the present invention, of thesedrugs as well as other neuroprotective drugs that may yet be discoveredor are currently under investigation.

Various embodiments of the present invention further include steps ofmapping the subject's brain activity and corresponding said brainactivity to movement the subject is performing or has performed. Suchmovement may be voluntary or involuntary, and/or normal or symptomatic.In order to understand the brain mapping process, it is important tounderstand the basic structures of the nervous system and how theyinteract. The neuron doctrine provides a descriptive and informative setof information regarding neurons, the nerve cells tasked withtransmitting nerve impulses within the nervous system. The neurondoctrine states that the brain is made up of individual cells (neurons)that are very different from other cells and tissues in the body,partially in that neurons comprise specialized features such asdendrites, a cell body, and an axon, structures not contained in anyother type of cell in the body. Like most other cells, neurons contain anucleus, and the neuronal nucleus must have access to nutrition for thecell to remain alive; if one were to split or divide a neuron, only theportion with the nucleus will survive. Neurons can vary greatly in size,shape and structure as determined by their locations or particularizedand specialized function or role within the body. Nerve fibers are theresult of cell processes and the outgrowths of nerve cells wherebyseveral axons are bound together to form one nerve fibril, orneurofilament. Several nerve fibrils then form one large nerve fiber.Myelin, an electrical insulator, forms around selected axons to insulateand protect the axon. Adjacent or connected neurons are connected toeach other, not by continuity of cytoplasm or physical contact betweenthe cells, but rather by a contact point across which the cellscommunicate by transmission of chemical or electrical signals viastructures called synapses. The axon, the transmission end of a neuron,is capable of transmitting such signals as well as receiving them, butthe system exhibits a preferred direction of communication from cell tocell—typically transmission from axon of one neuron and receipt of thesignal by the dendrite of the next neuron— and this is called the Law ofDynamic Polarization. Once two neurons make contact, a unity oftransmission exists such that contact can be either excitatory orinhibitory, but will always be the same type of transmission and willnever switch, and each nerve terminal releases a single type ofneurotransmitter. Thus, when the signal is transmitted via the synapsebetween two neurons, it either excites the neuron into cuing an action,or inhibits the neuron and prevents or stops ongoing action—such asmovement of a muscle. These communications between neurons not onlycontrol the body's movement and functions, but also form thoughts,feelings, and the like. A very specific set of neurons, staring in thesubject's brain, must fire in a specific order to achieve the endresult, for example performance of a particular movement. Like all othertissues in the body are composed of individual cells, these neurons arethe individual cells that make up the various portions of the nervoussystem including the brain and spinal cord. Various parts of the brain(hemispheres, lobes, cortexes, etc.) and the spinal cord are employedfor many different functions of the body. With particular regard tomovement, the brain comprises a motor cortex which is involved invirtually all movement. The primary motor cortex, or M1, is one of theprincipal brain areas involved in motor function. M1 is located in thefrontal lobe of the brain, along a bump called the precentral gyms. Therole of the primary motor cortex is to generate neural impulses thatcontrol the execution of movement. Signals from M1 cross the body'smidline to activate skeletal muscles on the opposite side of the body,meaning that the left hemisphere of the brain controls the right side ofthe body, and the right hemisphere controls the left side of the body.Every part of the body is represented in the primary motor cortex, andthese representations are arranged somatotopically—the foot is next tothe leg which is next to the trunk which is next to the arm and thehand. The amount of brain matter devoted to any particular body partrepresents the amount of control that the primary motor cortex has overthat body part. For example, a lot of cortical space is required tocontrol the complex movements of the hand and fingers, and these bodyparts have larger representations in M1 than the trunk or legs, whosemuscle patterns are relatively simple. This disproportionate map of thebody in the motor cortex is called the motor homunculus. Other regionsof the cortex involved in motor function are called the secondary motorcortices. These regions include the posterior parietal cortex, thepremotor cortex, and the supplementary motor area (SMA). The posteriorparietal cortex is involved in transforming visual information intomotor commands. For example, the posterior parietal cortex would beinvolved in determining how to steer the arm to a glass of water basedon where the glass is located in space. The posterior parietal areassend this information on to the premotor cortex and the supplementarymotor area. The premotor cortex lies just in front of (anterior to) theprimary motor cortex. It is involved in the sensory guidance ofmovement, and controls the more proximal muscles and trunk muscles ofthe body. In our example, the premotor cortex would help to orient thebody before reaching for the glass of water. The supplementary motorarea lies above, or medial to, the premotor area, also in front of theprimary motor cortex. It is involved in the planning of complexmovements and in coordinating two-handed movements. The supplementarymotor area and the premotor regions both send information to the primarymotor cortex as well as to brainstem motor regions. Neurons in M1, SMAand premotor cortex give rise to the fibers of the corticospinal tract.The corticospinal tract is the only direct pathway from the cortex tothe spine and is composed of over a million fibers. These fibers descendthrough the brainstem where the majority of them cross over to theopposite side of the body. After crossing, the fibers continue todescend through the spine, terminating at the appropriate spinal levels.The corticospinal tract is the main pathway for control of voluntarymovement in humans. There are other motor pathways which originate fromsubcortical groups of motor neurons (nuclei). These pathways controlposture and balance, coarse movements of the proximal muscles, andcoordinate head, neck and eye movements in response to visual targets.Subcortical pathways can modify voluntary movement through interneuronalcircuits in the spine and through projections to cortical motor regions.The spinal cord is comprised of both white and gray matter. The whitematter consists of nerve fibers traveling through the spine. It is whitebecause the nerve fibers are insulated with myelin for faster conductionof signals. Like many other large fiber bundles, the corticospinal tractcourses through the lateral white matter of the spine. The inside of thespinal cord contains gray matter, composed of the cell bodies of cellsincluding motor neurons and interneurons. In a cross-section of thespinal cord, the shape of the gray matter resembles a butterfly. Fibersin the corticospinal tract synapse onto motor neurons and interneuronsin the ventral horn of the spine. Fibers coming from hand regions in thecortex end on motor neurons higher up in the spine (in the cervicallevels) than fibers from the leg regions which terminate in the lumbarlevels. The lower levels of the spine therefore have much less whitematter than the higher levels. Within the ventral horn, motor neuronsprojecting to distal muscles are located more laterally than neuronscontrolling the proximal muscles. Neurons projecting to the trunkmuscles are located the most medially. Furthermore, neurons of extensors(muscles that increase the joint angle such as the triceps muscle) arefound near the edge of the gray matter, but the flexors (muscles whichdecrease the joint angle such as the biceps muscle) are more interior.It is important to note that a single motor neuron in the spine canreceive thousands of inputs from the cortical motor regions, thesubcortical motor regions and also through interneurons in the spine.These interneurons receive input from the same regions, and allowcomplex circuits to develop. Signals generated in the primary motorcortex travel down the corticospinal tract through the spinal whitematter to synapse on interneurons and motor neurons in the spinal cordsventral horn. Ventral horn neurons in turn send their axons out throughthe ventral roots to innervate individual muscle fibers. In thisexample, a signal from M1 travels through the corticospinal tract andexits the spine around the sixth cervical level. A peripheral motorneuron relays the signal out to the arm to activate a group ofmyofibrils in the bicep, causing that muscle to contract. Collectively,the ventral horn motor neuron, its axon, and the myofibrils that itinnervates are called a single motor unit. Each motor neuron in thespine is part of a functional unit called the motor unit. The motor unitis composed of the motor neuron, its axon and the muscle fibers itinnervates. Smaller motor neurons typically innervate smaller musclefibers. Motor neurons can innervate any number of muscle fibers, buteach fiber is only innervated by one motor neuron. When the motor neuronfires, all of its innervated muscle fibers contract. The size of themotor units and the number of fibers that are innervated contribute tothe force of the muscle contraction. There are two types of motorneurons in the spine, alpha and gamma motor neurons. The alpha motorneurons innervate muscle fibers that contribute to force production. Thegamma motor neurons innervate fibers within the muscle spindle. Themuscle spindle is a structure inside the muscle that measures thelength, or stretch, of the muscle. The golgi tendon organ is also astretch receptor, but it is located in the tendons that connect themuscle to the skeleton. It provides information to the motor centersabout the force of the muscle contraction. Information from musclespindles, golgi tendon organs and other sensory organs are directed tothe cerebellum. The cerebellum is a small grooved structure located inthe back of the brain beneath the occipital lobe. This motor region isspecifically involved when learning a new sport or dance step orinstrument. The cerebellum is involved in the timing and coordination ofmotor programs. The actual motor programs are generated in the basalganglia. The basal ganglia are several subcortical regions that areinvolved in organizing motor programs for complex movements. Damage tothese regions result in spontaneous, inappropriate movements. The basalganglia send output to other subcortical brain regions and the cortex.

Understanding such structure and function of neurons facilitates brainmapping by the knowledge of what is happening within the brain andnervous system as it appears through, for example, various neuroimagingtechniques during the mapping process. Within the scope of the presentinvention, particularly focusing on movement disorder therapy,monitoring the brain as a subject performs particular movements orexperiences particular symptoms can help provide a framework and guideto the functions of the subject's brain as they correlate to suchmovements or symptoms. Electrochemical responses may be observed andrecorded to indicate neuronal activity. As neurons are activated, theyexhibit a hemodynamic response in the form of rapid delivery of blood toactive neuronal tissues and the neuron transmits a Blood OxygenationLevel Dependent (BOLD) signal that corresponds to the concentration ofdeoxyhemoglobin within the neuron. Thus, as numerous neurons in aparticular area of the brain are activated, they BOLD signal increasesfor that area based on the increased blood flow to each of the activeneurons there. Imaging modalities may then be used to detect thisincreased blood flow, for example fMRI, and can then provide an image ofthe areas of the subject's brain that are activated in response to aparticular stimuli or variable. Another option is to observe and recordelectrical responses to neuronal activity. Evoked electrical potentials,generated from the occurrence of a specific event or application of acatalyst, can be measured using sensors such as electrodes (implanted ornon-invasive, surface electrodes), such as with use of anelectroencephalogram (EEG). Multiple types of evoked potentials areknown and characterized based on the response-eliciting event, be itsensory (somatosensory), cognitive or motor in origin. Positive andnegative voltages may be recorded by the electrodes, typically in therange of 10μ to 100μ volts, and voltage swings are separated intopositive and negative values, as well as by time in which they wererecorded after the event or stimulus has occurred. The voltages mayalternatively be labeled in order and characterized as positive ornegative. The voltages are representative of the output or activity ofthe neurons in response to the stimulus or event (e.g., particularmovement). Still another alternative may be to map magnetic fieldsproduced from electrical currents that naturally occur in the subject'sbrain in order to resolve time courses of brain activity.Magnetoencephalography, but measuring these magnetic fields, is capableof resolving events in 10 milliseconds or less, and is particularlysuited for brain activity mapping in the primary auditory, somatosensoryand motor cortexes and areas. Each of these, and other imagingmodalities can be used alone, or in combination with each other, inorder to identify portions or structures of the subject's brain that areactivated or deactivated by a particular event or occurrence, such as aparticular movement or movement disorder symptom.

It is important to note that within the scope of the present invention,brain mapping is a separate and wholly different concept than that ofthe tuning maps described herein. Tuning maps are visual representationsof objective scores indicating the severity of a subject's movementdisorder symptoms as a result of numerous variables including therapystimulation parameters. Brain mapping, and resultant brain activitymaps, are maps of measured or detected electrical activity of the brainindicating the location and strength or intensity of such activity ofelectrical activity of the brain. The tuning maps are a graphicalrepresentation of calculated symptom severity scores as calculated byone or more algorithms as a result of measured signals from sensorswhereas the brain maps or brain activity maps are representations ofmeasured electrical activity of the brain directly obtained (possiblywith some pre-processing and processing) directly from sensors.

Brain mapping, for the purposes of the present invention, can beperformed by various imaging methods, each with varying degrees ofinvasiveness. Surface imaging techniques, such as EEG signals acquiredvia surface sensors or electrodes, is a common method of detecting andmapping a subject's brain activity. The surface-acquired EEG signals maybe localized to a general or more particular region of the brain fromwhich the electrical activity is sensed and acquired, and thus a map maybe generated providing an indication of the regions of the brain thatare excited and utilized at various points in time. Another method, moreinvasive than surface EEG or other such surface imaging techniques, iselectrocorticogram (ECoG) signal acquisition. Like EEG, ECoG also can beused to acquire brain activity signals, but ECog involves theimplantation of sensors or electrodes directly onto the surface of thesubject's brain. Because of the implanted nature of the electrodes usedfor obtaining EEG signals, ECoG is sometimes referred to as intracranialelectroencephalography (iEEG); it acquires essentially the same signalsas traditional, surface EEG but with implanted brain surface electrodesas opposed to external surface electrodes. Given the direct placement ofECoG sensors on the surface of the subject's brain, ECoG may be moreaccurate and precise in the measurement of brain activity thattraditional EEG due to the additional layers of tissue (cranium, blood,skin) that separate the subject's brain from traditional EEG sensors,where ECoG can measure directly from the surface of the brain. Eithertype of imagine may be used in order to obtain brain activity data,however, and both are commonly accepted methods of acquiring suchinformation. Accordingly, brain mapping for the purposes of the presentinvention may be performed using either of these, or other such imagingtechniques known to acquire and monitor brain activity from the externalsurface or internally from the surface of the subject's brain. Whilebrain activity can be monitored and mapped by external surfaceelectrodes or internal, brain surface electrodes, the resolution of suchimages is generally low, and is certainly not sufficient to get a clearpicture of what specific neurons or bundles of neurons are operating tocreate a certain motion or cause a particular symptomatic movement. Lowresolution brain mapping is useful for general brain-region excitationidentification, but much higher resolution is required to truly performa safe, accurate and efficacious programming or tuning function fortherapy devices. Therefore, the present invention preferably employsimplanted sensors located within the subject's brain to detect andacquire signals relating to activation of the neurons within thesubject's brain. Electrocorticography systems utilize implanted sensorson the surface of the subject's brain, and have been used to sense brainactivity in order to map such activity. Electrocorticography systems,however, acquire signals from a vast amount of neurons at once, on theorder of hundreds of thousands of neurons, and thus the resolution isstill too low for discernment of targeted brain regions, structures, andneurons that are attributable to a given even, such as a particularmovement. Embodiments of the present invention that employ brain-mappingto facilitate the therapy delivery process preferably obtains higherresolution brain mapping images, correlated to smaller bundles ofneurons or even individual neurons that correlate to movements orsymptoms of interest. In order to obtain such high resolution brainmapping images, such embodiments of the present invention may utilizeeither separate electrodes, sensors or leads for acquiring brainactivity data, or dual-mode stimulation/sensing leads implanted into thesubject's brain. More specifically, the DBS electrodes each preferablycomprise multiple contacts disposed along the length of each DBS leadwhere each contact is not only capable of providing an electricalcurrent stimulation to the subject's brain, but is also capable ofsensing or acquiring signals from the subject's brain. Such acquiredsignals are preferably representative of brain activity in the immediatevicinity of the contact's location within the subject's brain such aslocal field potentials or single-/multi-units responses. Thus, thepresent invention utilizes dual-mode DBS leads which comprise multiplecontacts each capable of both sensing signals and providing electricalstimulation.

Thus, the systems and methods of the present invention may include thestep of mapping the subject's brain activity, utilizing the abovedisclosed methods or those known in the art, in order to determine theareas and regions, potentially down to the level if bundles of neuronsor individual neurons, that are employed to elicit a certain action orevent from the subject, such as movement. Initial, or any subsequent,brain mapping performance may be performed in a guided session wherebythe subject is instructed to perform a specific movement or task whilethe dual-mode DBS leads acquire signals from the brain to determine whatpart(s) of the brain caused that motion or activity to occur. Althoughdirected and instructed movements may be used, preferably the subject'smovement is simultaneously measured by external sensors such asdescribed herein. In this manner, an initial programming session mayeliminate the variables of discretionary or complex movements, and allowthe system to measure external body motion with the sensors whilesimultaneously acquiring brain activity data to correlate the brainactivity with the known, instructed motion as well as with the measuredexternal body motion obtained from the external sensors. In this manner,a baseline can be formed by which the system identifies and recognizesparticular motions of the subject's body and measures them using theexternal sensors, and then “knows” based on the correlation with thebrain activity map what motion(s) or movement(s) are being performed andwhich areas of the brain are used to cause them.

The use of known, directed or instructed tasks is not, however,necessary, given that the external body motion sensors alone may besufficient to identify particular movements or motions and to create thecorrelation with brain activity. As the system is used over a period oftime, particularly in real-life settings of the subject performingactivities of daily living with the external sensors measuring thesubject's external body motion and the implanted dual-mode DBS leadsmeasuring brain activity, the system can preferably learn from suchcontinuous use and associate patterns of brain activity with specificexternal boy movements. Preferably the system comprises nonvolatileinternal memory that can be used to store data related to the externalbody motion as well as the brain mapping data, creating a databasecomprising the data with marking information (e.g. time data) so thatthe data can be cross-referenced to see the correlation. Preferably thecorrelation is also calculated, using a movement and brain activityalgorithm in real-time and stored along with the data related toexternal body motion and bran map activity. Iterative movements andmeasurements can thus be correlated and later accessed and/or comparedto determine what movement the subject was performing or what areas ofthe subject's brain were responsible for movement. As the systemmonitors more and more complex movements over time, a large database maybe compiled that effectively links individual components of a subject'smovement (e.g., movement of the index finger vs. movement of the wholearm) to the portions of the brain that are responsible for causing suchcomponents of movement. By extension, the external body motion sensorswill not only measure calculated, normal and deliberate movement, butwill also capture involuntary and instinctive movement, as well assymptomatic movement. Repeated iterations of the measurements of bothbody movement and corresponding brain activity will help the systemresolve a distinct and accurate map of the particular portions,structures, or even neurons of the subject's brain that cause each typeof movement to occur, including symptoms.

This learning process can greatly be facilitated by an initial trainingprotocol such as described above wherein the system is used to measureboth external body movement and corresponding brain activity under knownconditions while the subject performs directed, instructed movements,tasks or activities. The baseline created from the training data setcreates an initial data set where the particular movement is known andcan be immediately correlated and identified as being caused by themeasured and observed brain activity measuring during performance of theprotocol. The movement and brain activity correlation algorithm(s)(correlation algorithms) are thus preferably machine learning algorithmsdesigned to see the relationship between two very large bodies of data.One example of types of correlation algorithm that can be used is asupervised algorithm whereby the algorithm comprises a target or outcomevariable (or dependent variable) (such as a correlation index orqualified definition that certain movements are caused by certainportions, structures or neurons of the brain) which is to be predictedfrom a given set of predictors (the measured external body movement dataand brain activity/brain map data). Using these set of variables, thealgorithm generates a function that maps inputs to desired outputs. Thetraining process continues until the model achieves a desired level ofaccuracy on the training data as indicated by accurate identification ofthe brain portions that cause the movement. Examples of supervisedlearning algorithms include regression algorithms, decision treealgorithms, random forest algorithms, k-nearest neighbor (KNN)algorithms, logistic regression algorithms, and the like. Anotherexample would be unsupervised algorithms in which target or outcomevariable to predict or estimate is required. Unsupervised algorithms arebest used for clustering populations in different groups, such assegmenting types of movement into identifiable groups with identifiablecharacteristics (e.g., arm movements, left hand movements, etc.).Examples of unsupervised learning algorithms include the Apriorialgorithm, K-means clustering algorithms, and the like. Still anotherexample of types of algorithms that may be used as correlationalgorithms within the scope of the present invention includesreinforcement learning algorithms with which the machine is trained tomake specific decisions whereby the machine is exposed to an environmentwhere it trains itself continually using trial and error (such as bycomparing calculated correlations with known correlations obtainedduring an initial training session). The system learns from pastexperience and tries to capture the best possible knowledge to makeaccurate business decisions. Examples of reinforcement learningalgorithms include the Markov Decision Process. This, and otheralgorithms known to those skilled in the art, can be used alone or incombination to help identify from the various sets of measured data whatportions of the brain cause certain movements to occur—either normal orsymptomatic.

As the system is used continually over a period of time, the amount ofmeasured data and the correlations between the myriad measured datapreferably create a vast and robust trained algorithm tied to thedatabase that is able to identify in real-time a movement or motion frommeasured brain activity in a particular pattern, or to identify theareas of the brain that caused a particular detected or measuredmovement to occur. The database may be local within the one or morecomponents of the device, or may be a remote or cloud-based database.Preferably, the system and algorithm(s) are also able to discern betweennormal and symptomatic movement, thus identifying symptomatic movementas the portions of the brain that might be contributing to theoccurrence of symptoms or the over-arching disease or disorder.Ultimately, in some embodiments, after sufficient training of thealgorithm has occurred, the external movement sensors may be able to beremoved from operation of the system. In such embodiments, the systemwould be able to identify the occurrence of a particular movement ormotion—most notably symptomatic movement or motion based solely on aparticular pattern of brain activity.

The brain mapped data may then be used in the therapy tuning processesdescribed herein. Again, the dual-mode DBS leads, each preferably with aplurality of contacts, are used not only to sense brain activity (whichis then correlated with external body movement sensor data and our knowninputs related to prescribed movement), but to provide electricalstimulation to the subject's brain. The exact form of the electricalstimulation provided may be influenced by measured movement fromexternal body motion sensors as well as the measured or detected brainactivity from the dual-mode DBS leads. Based on either measured externalbody movement and/or sensed brain activity the system preferably outputsa desired set of therapy parameters or settings tailored to address theparticular state of the subject. In the present embodiments utilizingbrain activity mapped data, the process is essentially similar to thatdescribed throughout regarding measured movement data, tuning maps, andthe like, but with either brain-mapped data instead of theexternally-sensed movement data and/or tuning maps, or in conjunctionwith such measured movement data. The subject's movement and/or brainactivity are measured and symptoms severity is scored based on themeasured symptomatic movement, or identified symptomatic movement in thebrain activity data. Again, the system is able to identify suchsymptomatic movement after correlating movement data and/or otherphysiological sensor data with sensed brain activity for the particularpatient. Based on the symptom severity, the system may provide an outputcomprising a new or second level of therapy parameters or setting thatmay be applied to the subject's DBS device in order to provide suchtherapy to the subject. Embodiments utilizing mapped brain activity datamay be able to provide more accurate and finely-tuned therapystimulation to the subject. This increased accuracy and precision is dueto the high-resolution brain activity mapping that causes the presentinvention to exhibit a more educated and precise identification of theparts of the subject's brain which are related to the symptomaticmovement. Thus, utilizing mapped brain activity data, not only can theattributes of the stimulation (e.g., amplitude, frequency, etc.) beadjusted to address the target area of the brain, but the stimulationfield can be shaped more precisely and accurately in order to targetthat portion of the brain and minimize the stimulation's effects onother areas of the brain, and thus also minimize occurrence of sideeffects. Thus, brain activity mapping may be used to augment and enhancethe external movement measurement embodiments described herein, eitheropen loop with clinician input, semi-closed loop, or closed loop.

Additionally, it is envisioned that, after time using the system andbuilding a strong and robust database of mapped brain activitycorrelated to measured and/or known movement data, other embodiments maynot require or utilize external body movement sensors, and may relysolely on the dual-mode DBS leads. In such embodiments, the systemsenses and maps brain activity, and when such brain activity indicatesthat symptomatic movement is occurring, decides whether to adjust thetherapy parameters in order to address that symptomatic movement. Aswith the other embodiments, the suggested therapy parameters may beoutput for clinician review, or may be automatically implemented andprogrammed into the subject's DBS device. Such embodiments allow forreal-time, finely-tuned and specifically targeted DBS therapy to bedelivered as a substantially immediate response to the detectedoccurrence of the symptomatic movement at the origination point in thesubject's brain.

The above systems, devices, and methods are further contemplated for usein treating various mental health disorders, particularly majordepression, bipolar disorder, and obsessive compulsive disorder. Inparticular treatment of mental health disorders would benefit from thepatient screening system and method for determining if the patient wouldbenefit from DBS therapy in dealing with his or her disorder, as well asthe integrated and intelligent programming systems and methods for bothin-clinic and remote programming of the DBS device once implanted.

Now referring to the drawings and figures, FIG. 1 illustrates thetherapeutic device programming (or “tuning,” or “parameter settingsadjustment”) process with one embodiment of the invention. A subject 1has a therapy device (not shown), which in the illustrated case is atherapy device for the treatment of a movement disorder, such as animplanted DBS device. Subject 1 wears a movement disorder diagnosticdevice comprising a sensor unit 2 and a command module 3. The sensorunit 2 comprises at least one sensor(s), preferably a physiological ormovement sensor(s), such as accelerometers and/or gyroscopes (both notshown), or other similar sensors, as well as a transmission system (notshown). In one preferred embodiment, the sensor unit 2 comprises threeorthogonal accelerometers and three orthogonal gyroscopes, or morepreferably at least one 3-axis accelerometer and at least one 3-axisgyroscope. Preferably, where the at least one sensor is an accelerometerand/or a gyroscope, these are micro-electrical-mechanical (MEMS)accelerometers or gyroscopes. In a preferred embodiment, a single chipcontaining both a 3-axis accelerometer and a 3-axis gyroscope is used,rather than using separate sensors. An example of such a combined sensorchip is the Invensense MPU-6000. The transmission system may be wired orwireless, and may communicate via any medium and any transmissionprotocol known to those skilled in the art. In the illustratedembodiment, the sensor unit 2 communicates sensor readings to a commandmodule 3 over a small flexible transmission cable 4, though thistransmission could also be conducted wirelessly. In the more preferredembodiment where both the sensor unit 2 and command module 3 arecombined in a single housing constituting the entire movement disorderdiagnostic device, the two modules may be integrated into the sameelectronics thus eliminating the need for wired or wirelesscommunication between separate modules. In the illustrated embodiment,the sensor unit 2 is worn on the middle phalange of the middle fingerand the command module 3 is worn on the wrist using a wristband, thoughthe placement of the sensor unit 2 and command module 3 may varydepending upon the symptoms of the movement disorder. Alternateplacements could include other fingers, the ankle, foot, shoulder, orelsewhere on the trunk of the body or on any part of any extremity.While the illustrated embodiment shows the sensor unit 2 and the commandmodule 3 as having separate enclosures, permitting for a lighter-weightsensor unit 2 that is easily worn on the finger, in alternateembodiments the sensor unit 2 and command module 3 may be integratedinto a single enclosure. In such embodiments where the sensor unit andcommand module are combined into a single enclosure forming the movementdisorder diagnostic device, all components of each unit are enclosed orattached to the single enclosure, including, but not limited to theunits and modules themselves, any power supply and communicationelectronics required for operation.

The command module 3 may provide numerous functions including, but notlimited to supplying power to the sensor unit 2, storing data in memory,transmitting data. Preferably, it is controlled by firmware inprocessor, for example an Analog Devices ADuC7020 processor. The dataacquisition (DAQ) section samples finger sensor unit data at 128 Hz foreach of the six channels. Optional onboard memory preferably provides atleast 12 hours of data storage. Some embodiments do not contain internalstorage, but rather transmit the data substantially in real-time to areceiver unit 5, a centralized database (not shown) or to a cloud-baseddatabase (not shown). Still other embodiments utilize onboard, temporarydata storage as well as substantially real-time data transmission to areceiver unit 5, centralized database (not shown) or a cloud-baseddatabase (not shown). A lithium-based battery provides at least 12 hoursof continuous use and is rechargeable by a computer through a LEMO, orsimilar connector, to USB connector cable. The command module 3 alsointegrates a membrane switch label (not shown) with LED indicators forpower and charging (not shown). Three membrane switches inside the label(not shown) provide on/off control and two subject diary inputs. Thecommand module 3 may perform rudimentary signal processing, such asfiltering and analog-to-digital conversion, on the movement signalsreceived from the sensor unit 2 before transmitting the movement signalsto a receiver unit 5. The receiver unit 5 may be of any type known tothose skilled in the art, and useful for receiving data from the sensorunit and making it available to a clinician, physician or technician oncomputer device 6. The computer device 6 will be referred to as a tablet(or tablet computer), but it is meant to be understood that it may beany such similar device, including, but not limited to desktopcomputers, laptop computers, tablet computers, personal digitalassistants (PDAs), “smart” cellular telephones, or the like. Thistransmission may be wired, but is preferably wireless, advantageouslyproviding the subject the greater comfort and convenience of beinguntethered as well as endowing the system with enhanced safety andportability. The wireless link frees subject motion, which allowsunimpeded and accurate assessment of subject symptoms. In an operatingroom, a small untethered system has the added benefits of reducingfurther subject discomfort and not impeding clinical traffic. A wirelesssystem, which is not directly connected to any source of AC power, hasthe added benefit of reducing or eliminating risk of electrical shock.Preferably, the wireless transmission is robust and operates in afrequency band designated for hospital or clinical-setting use.Preferably, the wireless transmission radio is a Bluetooth radiooperating in the 2.4 GHz band. More preferably, radio transmissionoccurs over the Wireless Medical Telemetry Service (WMTS), dedicated bythe FCC to wireless medical equipment used in hospitals, which comprisesthe frequencies 608 to 614 MHz, 1395 to 1400 MHz and 1429 to 1432 MHz.Preferably, radio communication is accomplished using a mix oftraditional heterodyning techniques along with newer software radiotechniques. For example, receiver structure consists of a band selectfunction of either 608-614 MHz or 1395-1432 MHz, followed by aheterodyning operation. The lower frequency band undergoes one frequencytranslation while the upper undergoes two frequency translations. Forthe low band (608-614 MHz) the signal is translated to 44 MHz where itis then sampled by an A/D converter and demodulated in the “sampled”domain. The high band is translated first to the lower frequency band(608-614 MHz) and processed in the same fashion. The software radiodemodulation approach accommodates many different data rates andmodulation formats and advantageously allows future radio upgrades to beimplemented simply by changing the signal processing program opposed tonecessitating an entire analog hardware redesign. The low band transmitsignal is a simple frequency source modulated with appropriateinformation. For the high band transmit signal, the same signal used forthe low band transmit signal is mixed with a high frequency signal toproduce the desired output. For transmitter operation, the signalprocessing hardware generates the modulating signal for all differentsignal formats and data rates. The signal processing hardware outputs amodulating signal input to an oscillator circuit that creates themodulated transmit signal. The modulated signal, for the high band, usesthe low band modulator and translates that signal to the properoperating frequency. Since the modulator is the same for both low andhigh bands it ensures the same signal quality regardless of operationband. Since the radio is a transceiver (two-way link), the design canserve as a master or slave; thus the same design can be employed in thecommand module 3 as well as in the receiver unit 5.

Data may also be collected in an on-board memory contained within thecommand module 3. Such onboard or internal memory may be used fortemporary storage so that the data may be saved and then downloaded tothe tablet computer 6 later, advantageously allowing the subject to wearthe movement disorder diagnostic device comprising sensor unit 2 andcommand module 3 for more prolonged symptom monitoring. Additionally, orin the alternative, the onboard memory may be used to temporarily storethe movement data and provide a backup in the event of halted,corrupted, or otherwise incorrect transmission of the data from themovement disorder diagnostic device comprising sensor unit 2 and commandunit 3 to the receiving unit 5.

The receiver unit 5 may be, and is preferably integrated into somelarger system—for example, it may consist of a wireless receiver, suchas a Bluetooth receiver, integrated into a device such as a laptop ortablet computer, a cellular phone, etc.—or it may be a separate devicebuilt into an enclosure. However, in the illustrated embodiment, thereceiver unit 5 is connected to a tablet computer 6 via one of the USBports (not shown, in a dongle-style connection that advantageouslyeliminates a cable), is powered thereby, and comprises a radio frequencytransceiver capable of 2-way radio frequency communication with thecommand module 3. Power regulation and USB-based data transmissionprotocols may be among any known in the art. The receiver unit 5 may be,in some embodiments, an off-the-shelf Bluetooth USB adapter dongle.

The tablet computer 6 is used to collect data transmitted from thecontrol module 3, allow user inputs to store and track motor performanceand therapy device parameter settings, and provide clinicians withreal-time symptom quantification feedback. The tablet computer 6 of theillustrated embodiment may be any computing device with a user interface7, including a smart phone, PDA, laptop computer, desktop computer,iPhone, iPad, or the like. Preferably, the tablet computer 6 islightweight and portable, allowing for its easy transport within anoperating room or other setting where the clinician, physician ortechnician would utilize the device, and includes a touch screen. Insome embodiments, the tablet computer 6 may be equipped with a clip orhanger (not shown) for easy mounting to, for example, an operating roompole. Most preferably, the tablet computer 6 is any mobile device thatthe clinician, physician or technician can utilize remotely from thesubject by receiving any data communicated from the subject's movementdisorder diagnostic device, a database, or other sensors or systems usedto measure, monitor, or record the subject's movements. The tabletcomputer 6 allows the clinician, physician or technician to access thedata and review and/or analyze it wherever he or she may be, and withoutrequiring the subject to be located in the immediate location orvicinity.

The user interface 7 may be visual, preferably comprising a touchscreen, or it may be an audio interface that accepts and transmitsspoken commands. In addition, or alternatively, the user interface maybe used to provide an automated testing protocol to the subject 1 byproviding instructions to the subject 1 on which movement disordertest(s) to perform, and how to perform them. In preferred embodiments,the subject 1 may be instructed on which tests to perform and/or how toperform them on a separate display, not on the tablet's user interface.In such embodiments, the subject 1 and clinician, physician ortechnician preferably have separate devices with user interfaces suchthat the subject can receive instructions on movement disorder tests toperform while at home or otherwise remote from the healthcareprofessionals, and the clinician, physician or technician can access thesubject's movement data while remote from the subject. The userinterface 7 preferably provides several key components and an overallsoftware wrapper. First, it preferably provides a main menu (not shown)to access all software features including a subject database (notshown), the tuning assistant software, which runs the therapy deviceparameter settings tuning algorithm, and software for automaticallygenerating clinical reports following tuning sessions. Next, itpreferably provides a module to view real-time motion data transmittedby the movement disorder diagnostic device comprising sensor unit 2 andcommand module 3, helping ensure proper setup and communication prior toclinical therapy device programming. The user interface 7 alsopreferably communicates with the system registry to store systemparameters and clinician preferred settings. Finally, a help menu (notshown) with troubleshooting guides and frequently asked questions ispreferably included.

Subject data management is an important aspect of clinically-usedembodiments of the present invention. Preferably, the format of thesoftware used with the system is designed for a high volume subjectdatabase. Any database known in the art may be used but is preferablyone which scales well to accommodate thousands or tens of thousands ofsubjects. Preferably, the database has fields for subject history,including the subject's surgery dates, a running list of the subject'sclinical sessions (past and/or future scheduled), the subject's primaryphysician, neurologist, medication dosage, etc. Preferably, the subjectis also programmed with the ability to import e-mails and otherdocuments into the subject history, and to export a standardized patientinformation sheet (reporting). Preferably, the database is programmed soas to permit all stored subject information to conform HIPAA guidelinesfor patient privacy and confidentiality.

A separate programmer device 8 is used in some embodiments by theclinician, physician or technician to remotely program the subject'stherapy device, that is, to adjust the therapy device's parametersettings. The separate programmer device 8 may be a separate device fromthe tablet 6, but more preferably the tablet is capable of providingboth functions (see FIG. 2 ). Whether the separate programmer device 8is separate or integrated, it communicates with the subject's therapydevice (e.g., DBS device), and transmits the desired therapy parametersto the subject's therapy device such that the therapy device operatesunder the transmitted parameters. Where the programmer device or unit isseparate from the tablet, preferably communication between them is bywireless methods as described above. In all embodiments, the programmerdevice or unit preferably communicates wirelessly with the subject'stherapy device.

In addition, or alternatively, the movement disorder diagnostic devicecomprising the sensor unit 2 and command module 3 may transmit to aserver or group of servers constituting a centralized database, such aswith cloud computing whereby the data resides on such server or group ofservers and can be accessed at the point of testing or some remotelocation for review by a clinician, physician or technician. Further,the tablet and/or programmer device or unit may also communicate withand transmit data to a centralized database or cloud-based database inorder to store the preferred therapy parameters for the particularsubject, as well as information regarding the testing and tuningprotocols used to arrive at the desired parameters. All the data that istransmitted and stored on a centralized database or cloud-based databaseis intended to be made accessible to the clinician, physician ortechnician for later review, for reference when the subject requiresadditional treatment or tuning, and to be readily available to otherclinicians, technicians or physicians who the subject may receivetreatment of any variety from and who might need to access the data inorder to properly and safely attend to the subject. For example, asubject may reside in one state through the summer months and receivetuning of the therapy device and treatment there, but then may travel toanother state for winter months and require similar attention there. Thedatabase storage of data allows clinicians, technicians or physicians inboth states to readily obtain access to the subject's data and toprovide the appropriate care to the subject. In all exchange ofinformation that occurs in the above example and in all otherembodiments of the present invention, it is important that informationbe exchanged securely and in ways that do not improperly disclose asubject's identity. Because of this, in certain preferred embodiments,all personal information of a subject is stored securely at a remotedatabase and is accessible only through a secure network connectionwherein both the database and connection protocol are compliant withstandards required by the health insurance portability andaccountability act (HIPAA). Often, this will require encryption of thedata to eliminate the possibility that the data can be read by a thirdparty and many preferred embodiments of the present invention includethe use of data encryption.

As indicated in the above example, various embodiments of the presentinvention involve sending a movement disorder monitoring device home orto another remote location with a subject to be used for movementdisorder testing away from a physician's or clinician's place ofpractice. This step likely occurs after initial programming of thedisplay unit as described above. Once the subject arrives home, themovement disorder monitoring device is placed in the subject's homewhere it may be powered by either a single or multiple on-boardbatteries or by another power source in the subject's home such as astandard 120 volt alternating current outlet. Once in the home thedisplay unit may, at intermittent times selected by the programmingphysician or clinician, alert the subject of the need to perform certainmovement disorder evaluation tasks. Alternatively the movement disorderdiagnostic device may be worn continuously allowing measurements andrecordings to be taken periodically, at scheduled intervals or times, orbased on stimulus or measurements that indicate the subject isperforming a particular activity, movement or motion, or is experiencingsome symptom or side effect of therapy. At these times, the display unitmay produce a sound, provide a visual alert on its display screen, or acombination of both as a way to alert the subject. In response to thealert the subject will place at least one sensor on his or herextremity(ies) as instructed by the display unit, if the diagnosticdevice containing sensors is not already being worn, and will proceed tofollow other instructions provided regarding how to properly completecertain tasks used to evaluate the severity of the subject's movementdisorder symptoms. Again, alternatively, in some embodiments orcircumstances, no particular task may be required, but the device maytake measurements and recordings while the subject is performingactivities of daily living. In certain embodiments, the subject may bevideo recorded by the camera of the display unit so that a physician canat a later time verify that the tasks were indeed correctly completed.Preferably, the subject will also answer other questions at this timeregarding a subject's self-assessment of his or her symptoms and thesubject's adherence to and use of treatments prescribed by the subject'sphysician or another clinician. Such questions may consist of inquiriesrelated to the subject's perception of the present severity of thesubject's symptoms, the subject's most recent dose ofpharmaceutically-based treatment, the subject's activity levelthroughout the day, and other similar pertinent information that isdesired to be known by the physician to help better understand asubject's symptoms. As noted above, however, in certain otherembodiments, the display unit may not be programmed to alert a subject,but instead may simply be left available for a subject to input dataregarding his or her symptoms or to select movement disorder assessmenttasks to perform from among various options according to the subject'spersonal preferences and schedule as well as the subject's ownsubjective view of the severity of his or her symptoms. The data fromthe instructed tasks or activities of daily living is then transmittedor communicated to a remote location (e.g., directly to the clinician,physician or technician, or to a database or server) where theclinician, physician or technician can access and analyze the data inorder to more accurately provide a next or second level of therapyparameters or setting that more directly addresses the subject's needs

In the embodiment illustrated in FIG. 1 , the subject 1 performs amovement disorder test according to instructions. Given the preferredembodiments involve remote monitoring, measuring and quantification ofthe subject's motor symptoms, the subject is preferably at a remotelocation, such as at home, when performing the movement disorder test(s)(or while performing the activities of daily living in someembodiments). In such embodiments with remote monitoring andmeasurement, instructions may be provided by an instructional video clipdisplayed on a user interface 7 of a tablet computer 6 (which isseparate from the tablet computer that is in the possession of theclinician, physician or technician), or on a separate display device(such as a home personal computer, smartphone, or other such device, notshown) advantageously providing the subject with a standardized visualaid to mirror while a test is conducted and data is collected.Alternatively, or in conjunction, the clinician, physician or technicianmay communicate with the subject via teleconference, or more preferably,video conference and thus provide instructions to the subject live.Video conferencing is preferred over teleconferencing to allow theclinician, physician or technician the ability to monitor and observethe subject as her or she performs the test(s) in order to ensure theyare performed correctly. Such a system implemented in software andprovided through user interface 7 ensures the same clinical examinationprotocol is used during subsequent test or programming sessions eitherin-clinic or in a non-clinical setting, advantageously allowingclinicians to more repeatedly and objectively track symptoms andassuring inter-subject data correspondence. In one embodiment, testingincludes (or may be limited to) three types of tremor tasks (resting,postural, and kinetic) and three types of bradykinesia tasks (fingertapping, hand grasps, and pronation/supination). Either alternatively orin addition, testing may include various gait/balance tasks, lowerextremity bradykinesia tasks, or other similar tasks as well. Themovement disorder diagnostic device, or more specifically the sensorunit 2 of the diagnostic device, collects data, which is sent to commandmodule 3 for transmission via radio link to a receiver unit 5. Theprocessor of the tablet computer 6 processes the movement data toextract kinematic features, which are then fed into a trained scoringalgorithm implemented as a software algorithm in the tablet computer 6.The trained scoring algorithm may output a score, which may thenoptionally be displayed on the user interface 7. A tuning algorithm oftablet computer 6 then computes suggested therapy device parameters orsettings based at least in part upon the current therapy deviceparameter settings and the collected movement data and/or the quantifiedscore computed therefrom. An exemplary tuning algorithm for computingthe suggested therapy device parameter settings is illustrated in FIG. 3. In many embodiments, the various algorithms utilized are able toanalyze the measured and quantified movement data in correlation to thetherapy parameters or settings being provided, determine if thoseparameters or settings or causing side effects to occur, and be able toanticipate similar parameters or settings that might cause the same sideeffect to occur. In such embodiments, the algorithm would then know toavoid the parameters or setting that are likely to cause the sideeffect, and thus avoid including them in the provided set or group ofparameters and settings.

Once suggested parameter settings adjustments are computed by the tuningalgorithm(s), the adjustments or new parameters or settings mayoptionally be displayed on the user interface 7. The tablet computer 6may communicate directly with the programmer device or unit 8, wired orwirelessly, to adjust the parameter settings. The therapy device may bereprogrammed wired or wirelessly, and typical implanted therapy devicesare enabled with means of wireless transcutaneous reprogramming. Atuning algorithm of tablet computer 6 then computes suggested therapydevice parameters or settings based at least in part upon the currenttherapy device parameter settings and the collected movement data and/orthe quantified score computed therefrom. One example of a tuningalgorithm for computing the suggested therapy device parameter settingsis illustrated in FIG. 3 . In many embodiments, the various algorithmsutilized are able to analyze the measured and quantified movement datain correlation to the therapy parameters or settings being provided,determine if those parameters or settings or causing side effects tooccur, and be able to anticipate similar parameters or settings thatmight cause the same side effect to occur. In such embodiments, thealgorithm would then know to avoid the parameters or setting that arelikely to cause the side effect, and thus avoid including them in theprovided set or group of parameters and settings.

Once suggested parameter settings adjustments are computed by the tuningalgorithm(s), the adjustments or new parameters or settings mayoptionally be displayed on the user interface 7. The tablet computer 6may communicate directly with the programmer device or unit 8, wired orwirelessly, to adjust the parameter settings. The therapy device may bereprogrammed wired or wirelessly, and typical implanted therapy devicesare enabled with means of wireless transcutaneous reprogramming.

The alternate embodiment of the invention depicted in FIG. 2advantageously combines the receiver unit 5, the tablet computer 6, theuser interface 7, and the separate programming device 8 into aprogrammer unit 9 having improved user interface 10, which is preferablya touch-screen interface. Preferably, the subject 1, and the clinicianare located remotely from each other. The command module 3 of themovement disorder diagnostic device transmits movement data acquired bythe sensor unit 2 of the movement disorder diagnostic device, asdescribed above, to the programmer unit 9, where the movement data isanalyzed and parameter settings adjustments are computed. Alternatively,or in conjunction with transmitting the data directly to the programmerunit, the data may be transmitted alternatively or simultaneously to aremote location, which may be a database or server (not shown), fromwhere the clinician, physician or technician may then access the dataimmediately or at a later time for review and/or analysis. The parametersettings may then automatically updated, with the programmer unit 9remotely interfacing with the therapy device (not shown) directly tocommunicate the updated parameters or settings to the therapy devicereprogram the therapy device's parameter settings.

Preferably, the touch screens of tablet computer 6 and programmer unit 9permit a user to interact with the user interface 7 or the improved userinterface 10 using a large sterile stylus (not shown), or the user'sfinger.

In alternate embodiments of the invention, quantification of movementdisorder symptoms may be performed using a different form of movementmeasuring apparatus. In one such example, a webcam built into the tabletcomputer 6 or programmer unit 9, or a video camera or set of multiplecameras connected thereto, view the subject 1 performing the motiondisorder test and feed video data into the tablet computer 6 orprogrammer unit 9 where, for example, machine vision algorithms measurethe motion of the limbs of the subject with respect to time according toany method known in the art. Such a method may consist, for example, indetermining marker points along the limb of the subject in order togauge relative motion, and such a method may be assisted by applyingmore visible markers (not shown) on various points on the limb of asubject 1, such as is common with motion capture technology. In suchcase, the need for the movement disorder diagnostic device comprisingsensor unit 2, with its accelerometers and gyroscopes, and commandmodule 3, may be obviated.

In one embodiment, an initial programming session will be carried outwhen the device is first provided to the subject according to a protocolcomprising the following steps. The clinician will assess all motor taskbaseline scores. The system or the clinician can remotely checkelectrode impedance for wire damage. This can be done be receivingperiodic signals corresponding to electrode impedance, though morepreferably (either alternatively or in conjunction with periodicsignals) allows the clinician to interrogate the device remotely andobtain necessary measurements and signals to determine or relate theelectrode impedance to the clinician at his or her remote location. Theclinician will record medication dosages, which information preferablyincludes information relevant to the subject's present level ofmedication, such as time and dosage of last medication administration.The clinician will select programming motor tasks, and in conjunctionwith the programmer device or unit 8, 9, the subject will repeat theseries of motor tasks for each stimulation setting. The DBS settings orparameters and corresponding scores for each chosen motor task will thenbe entered preferably remotely and automatically by the system, andwhere the clinician has the ability to switch between tasks for enteringdata and selecting which DBS parameters are fixed: frequency, current,pulse width, waveform type, contact setup (mono, bi, tripolar), and thelike, and the system communicates those parameters or settings to thetherapy device remotely without direct clinician interaction afterselection. Finally, the tuning algorithm(s) will assess all motor taskspost-programming, and the clinician will have the option of reviewing,and possibly editing the resultant parameters or settings. Preferably,for the clinician's optional review and editing, the system will providethe ability to enter DBS settings or parameters and scores completelyeither with a finger or stylus on a touch screen, and/or with a mouseand/or with a keypad or keyboard using the tab key to switch betweendata input fields. Preferably, the system provides three data inputmodes for clinician review and editing: (1) enter stimulation and scoreinformation, click update, enter next measurement; (2) enter informationand display updated tuning map; (3) use stylus/finger/mouse to click onthe tuning map for the appropriate measurement, with a new input boxappearing to enter score/side effects/notes. Optionally, the initialprogramming session may be performed without direct interaction with thetuning map, but rather where the algorithm(s) populate the tuning map,and the clinician, physician, or technician engages the optional reviewfunction to view the tuning map and/or the parameters or settings chosenby the algorithm(s) in order to approve or deny them based on thesubject's needs and the results from those therapy settings.

It is advantageous in some embodiments for the system to provide, or topermit the clinician performing the programming session to enter a largenumber of variables in order to provide a complete assessment of the DBStuning. The following is a representative list of information that maybe entered in each programming session: (1) general subject information,including patient ID, whether the subject's DBS implant is unilateral orbilateral, implant electrode site location and side; (2) motorevaluations performed during tuning, including (a) tremor: rest,postural, kinetic, (b) bradykinesia: finger tap, hand grasp,pronate/supinate, (c) rigidity: elbow/knee, head/neck, (d) leg agility:heel tapping, (e) rising from chair: with arms crossed, (f) posture, (g)gait: walking quality, (h) postural stability: pull back; (3) motorscores, in the form of integer scoring from 0 (no severity) to 4(extremely debilitating); (4) DBS settings or parameters, including, butnot limited to (a) contact: cathode/anode, monopolar, bipolar, tripolar,multiple channels with fractionalized control, waveforms, currentsteering, different waveforms, interleaving multiple waveforms, etc.,(b) stimulation parameters including amplitude (in volts), frequency (inHz), current (in amps), pulse width (in microseconds), the type ofwaveform of the stimulation impulse, (c) side effects and/or capsuleeffects, including (i) motor effects, such as worsening of symptoms,dyskinesias, facial pulling, (ii) non-motor effects, such as blurryvision, soft or slurred speech, sweating, headache, tingling(transient/non-transient), fatigue, sense of euphoria, paresthesia,and/or (iii) new or atypical side effects and update list of notableeffects.

FIG. 3 shows merely one optional example of a tuning algorithm used forcomputing suggested parameter settings adjustments. This basic tuningalgorithm utilizes symptom severity data, detected stimulation induceddyskinesias (SID), and clinical inputs such as clinician definedimprovement percentage (CDI %) to compute suggested stimulationparameter settings. Based on the typical clinical description, severalconstraints reduce the number of degrees of freedom in the tuningalgorithm. During DBS programming, the clinician or the algorithm mayutilize any subset of the motor task mentioned previously to evaluatemotor performance. The average tremor score (ATS) is computed for theset of tremor tasks and the average bradykinesia score (ABS) is computedfor the set of bradykinesia tasks utilized for a given iteration. Thisreduces the number of symptom severity outputs from a maximum of threeto one for each symptom. Dyskinesia is either “on” or “off.”

Recording symptom severity before the therapeutic device is turned onobtains baseline. In the case of DBS adjustment, the best monopolarelectrode contact is determined by finding the contact that provides thelargest therapeutic width, i.e., the largest change in supplied voltagefrom when a clinical benefit is noticed to when side effects occur. Thisis accomplished by fixing stimulation pulse width to initial settings,for example 60 μs, frequency to 130 Hz, selecting one contact, and thenstepping the voltage amplitude in small increments of approximately 0.2V. The procedure is repeated for each contact. The contact that providesthe largest therapeutic width is selected. With the pulse width (60 μs)and frequency (130 Hz) set to typical values, the clinician or thealgorithm then sets the amplitude to the lowest voltage that provides asignificant decrease in symptoms. If a satisfactory result is notachieved, pulse width or frequency may also be increased. This can be atime consuming iterative process that must be completed several timesover the first few months as microlesioning heals and requires acompensatory increase in stimulation amplitude to maintain clinicalbenefit. In various embodiments, the invention includes a sensitivetool, implemented in software and accessed through user interface 7 orimproved user interface 10 to detect the instant of clinical benefit asvoltage amplitude is increased and the instant any stimulation induceddyskinesias are detected. Use of the invention as a sensitive measure ofclinical benefit onset and side effect occurrence advantageously ensuresthe contact with the greatest therapeutic width is selected.

Once the contact width is selected, the initial parameter settingsadjustment iteration may be completed with literature-defined settingsof 60 μs and 130 Hz stimulation. Amplitude is set to 0.2 V initially,and then modified by the clinician or algorithm in subsequentiterations. After each stimulation parameter change, the clinician mayuse the user interface 7 or the improved user interface 10 to guide thesubject through motor tasks, or, in some preferred embodiments, thedevice will in an automated fashion provide instructions to the subjectvia a display to provide such guidance. The tuning algorithm outputprovides a suggested parameter direction output after each motor taskevaluation by utilizing the movement disorder quantification algorithm.The invention thereby maximizes clinical benefit by minimizing tremorand bradykinesia, minimizes adverse effects of stimulation-induceddyskinesias, and minimizes current consumption to maximize battery life.Thus, one objective function is to minimize the sum of average tremorscore (ATS) and average bradykinesia score (ABS), known as the summedmotor score (SMS) 11. This objective is achieved in the tuning algorithmby continuing to increase stimulation in the same direction as long asSMS is decreasing. A higher SMS corresponds to worse motor symptoms. Asecond constraint is that stimulation induced dyskinesias (SID) shouldnot occur. If they are detected, the direction of the parameter changeis reversed. Another system constraint is the minimization currentconsumption. This is accomplished by allowing a clinician definedimprovement percentage (CDI %) 12 and considering any changes of lessthan 5% in SMS to be insignificant. When these conditions are met, thecurrent parameter level is maintained 13 due to the SMS goal beingachieved and with consideration given to diminishing clinical returns,in order to maximize battery life. Once optimized amplitude has beenachieved or reaches 3.6 V, the clinician may adjust pulse width orfrequency utilizing the same algorithm. The chances of the feedbacksystem settling into local minimums are reduced by ensuring several ofthe settings are set at clinically accepted levels for the initialiteration and making only moderate adjustments as required.

While DBS programming frequently entails stepping through smallincremental changes, this process can be wastefully time-consuming ifthe motor symptom response of the subject indicates larger changes arerequired. The implementation of an artificial neural network 14 tooutput suggested stimulation parameters minimizes programming iterationsto reduce surgical and outpatient tuning session time.

Preferably, the artificial neural network 14 used in the tuningalgorithm used by some embodiments of the present invention is trainedwith recorded clinician-made stimulator parameter changes in response tomotor symptom severity changes during stimulator programming to minimizerequired iterations while still utilizing objective symptom severitymeasures to optimize performance. In this way, the algorithm takesclinician experience into account. Experienced clinicians are generallysuccessful in quickly reducing the number of potentially successfulparameter settings for tuning DBS systems. An expert clinician iscapable of recognizing severe motor symptoms and modifying a parameterby a larger magnitude, then when the symptom is less and onlyfine-tuning is required. The present invention is therefore capable ofquantitatively detecting motor symptom severity and suggesting aparameter change that approximates or mirrors the parameter change thatwould be made by an expert clinician.

Artificial neural network 14 may be implemented, for example, with theMATLAB Neural Network Toolbox offline using resilient backpropagationbatch training. Inputs to the neural network may include current andprevious stimulation settings 15 and motor responses.

FIG. 4 illustrates a two-layer network structure consisting of onehidden layer 17 with four neurons using “tansig” transfer functions andone output layer 18. As neural networks may fall into local minimumswhen being trained, each network is preferably trained three times withrandomized initial weights and biases and the best training results areselected. Additionally, early stopping improves network generalization.Data is separated into training and generalization sets to ensuretrained networks produce accurate results both when the training set isreapplied and also when it is generalized to new data. Preferably,training data is collected from multiple patients. To ensure that thesystem generalizes to new patients, network generalization can be testedby training the system using a jackknife “one left out” method. Usingsuch a method, the neural network is trained using data from, forexample, only nine of ten subjects. Data from the nine subjects in thetraining set is then reapplied to the trained network to ensure goodcorrelations while data from the “left out” subject is used to testgeneralization. The method is repeated, leaving out each subject onetime. For each training and generalization set, both the mean squarederror (MSE) and R-squared values between the clinician-made stimulatorparameter changes and those output by the system for each stimulationparameter are calculated. The MSE and R-squared for all training andgeneralization sets are averaged. Preferably, the system achievesnormalized MSE values of less than 10% and R-squared values of greaterthan 0.8 to show substantial agreement between system-suggestedsimulation parameter changes and clinician-made stimulation parameterchanges.

Preferably, separate data sets and acquired, and separate neuralnetworks are trained, for the surgical and outpatient scenarios.Preferably, the data used to train the algorithm averages the experienceof multiple expert clinician programmers.

Preferably, the tuning algorithm comprises a neural network asillustrated in FIG. 3 , but it might instead or in addition comprise oneor more of adaptive continuous learning algorithms, linear quadraticGaussian control, Kalman filtering, and model predictive control.

When the tablet computer 6 is connected to the Internet or similarcommunications network, wired or wirelessly, it may therefore transmitsubject data to remote systems, allowing general practitioners toconduct DBS programming remotely, minimizing travel for a subject 1 wholives far from a DBS implantation center or suitable programming clinic,so long as the subject 1 is equipped with the movement disorderdiagnostic device comprising sensor unit 2 and command module 3 andmeans of programming and/or making parameter settings adjustments to hisor her therapy device (including DBS implant).

FIG. 5 depicts a series specific display pages corresponding toreporting score provided for optional or periodic review by a clinician,physician or technician in various embodiments of the present invention.These examples of methods of reporting scores with visual displaysassociated with each display stage of the test process are merelyexemplary, and many variations of the display method, as well as thelabeling of the display, are envisioned. One example of displaying ascore for optional or periodic review is the expandable menu view 19,where the user (i.e., clinician, physician, or subject performingself-testing away from the clinician) is presented with a list of thedifferent types of movement disorders or movement disorder symptoms,which may or may not have been measured in a given test. In theportrayed example of this expandable menu view 19, the movement disordersymptoms that may be selected include tremor, bradykinesia, rigidity,gait and/or balance disturbances, and the like. The user is then giventhe option of expanding the results for each of those movement disordersor movement disorder symptoms through a series of levels (i.e., handthen to left or right), in order to view the score that was determinedfor each particular disorder or symptom in the indicated portion of thesubject's body. By way of clarification and example, the subject shownin menu view 19 received a score of 1 during rest for the symptom oftremor in the left hand, and a 2 for the pronation/supination task forbradykinesia in the left hand.

Another optional review display method, which may be independent or usedin conjunction with the expandable menu view is the tuning map 20. Atuning map 20 is generated for each task that the subject is directed toperform, symptom, or side effect and depicts the severity of thesymptoms measured in each sensor that is used for the given task. Eachtask, symptom or side effect that is performed may be represented on adifferent tab (i.e., tab A, tab B, tab C, where the lettered tabs inFIG. 5 either correspond to a task, symptom or side effect).Alternatively, the tab letters may be replaced by other labels orindicators, or even the name, or abbreviation thereof, of the task,symptom or side effect. Further alternatively or in addition, thedifferent tabs may represent combinations of tasks, symptoms (e.g.,averaged results of multiple symptoms), and/or combinations of sideeffects. In this particular embodiment, the amplitude 21 at which thetest was performed is measured in volts and indicated on one verticalaxis of the tuning map 20. Also in this particular embodiment, thecontact being used to provide therapy or stimulation is indicated on thehorizontal axis 23. However, in many embodiments, the axes may representany other test parameter or setting used, and in some preferredembodiments, one of the axes (typically the horizontal) may representdifferent groupings (see FIG. 6 ) of test therapy settings orparameters. In such embodiments, for example, the axis would provide arepresentation of a group (e.g., 1 representing group 1), which wouldcomprise a predetermined set of therapy parameters or settings beingtested, where the grouping may include variations of any of the abovedescribed therapy parameters or settings, such as contact, current,frequency, waveform, polarity, pulse width, and the like, as well ascombinations thereof. Some embodiments further allow the condition touse varying or comparative settings within the groupings. For example,it may be decided to combine the settings in such a manner to provideweighted scores where one symptom, task, or side effect is given agreater weight than another, but they are combined to create a singleweighted map. Similarly, therapy settings or parameters may be graduallyincreased or decreased as symptoms are continuously measured, ratherthan providing measurements or assessments at discrete amplitude levels.This allows a greater degree of freedom and versatility in defining thetest settings instead of being limited to one or two test parameters pertest. Such groupings decrease the amount of testing time required fortuning, and thus reduce cost to the subject or insurance company, aswell as opportunity cost of the clinician's time spent with a singlesubject. The calculated or estimated score 22 is depicted on a verticalaxis of the tuning map 20 as well, and is indicated as variouscross-hatch patterns. Alternatively, the score may be represented bycolors, shapes, or any other indicator. Each individual box that isshown represents a test performed 24. Preferably, the tuning map 20 isshown on a color display (not shown) for optional review and theseverity of the symptom is indicated by color. In this drawing, thecolors are represented by different types of shading or cross-hatchingrather than by the preferred color. Each column in the tuning map 20represents a different contact on the DBS probe. Therefore, eachindividual test box 24 depicts the results of performing a task whileadministering DBS at a prescribed voltage amplitude 21 and provides botha severity of the symptom that was detected or measured by virtue of thecolor (represented by the cross-hatching), which also correlates to agiven motor score. Additionally, each individual test box 24 may beselected, for example by pressing it on a touch-screen device, asrepresenting by the test boxes 24 which are outlined in black. When atest box 24 is selected, the user is able to see a detailed view (notshown) of the statistics and parameters of the test corresponding tothat box. In many embodiments, the clinician, physician or technicianmay be able to add notations to the different parameter or settinggroupings, or even to the individual test scores. Such notations mayinclude commentary or other notes regarding the efficacy of the givenparameter grouping or score, of side effects that occur, or any othernotations the clinician, physician or technician deem necessary.

A variable window 25 may display on the unit as well that allows theuser to input various conditions that have an effect on the test andtest results. These variables are calculated into the test results andhelp to give a more accurate calculated symptom score.

Other methods of displaying data corresponding to test therapy settingsor parameters and results may also be envisioned and are considered foruse with the present invention.

FIG. 6 portrays one example of the optional or periodic review tuningmaps 20 or other visual display tool or method for a particularembodiment with amplitude 21 on the vertical axis and groupings ofparameters or settings 23 on the horizontal axis, in greater detail.Each task performed, symptom or side effect is represented again by aseparate tab with its own tuning map 20. Though the tabs are labeled asA, B, C and A+B in the figure, in many preferred embodiments the tab maybe labeled with a number, the name of the task, symptom or side effectit represents, an abbreviation thereof, or some other label indicatingto the clinician, physician or technician what information isrepresented in the given tab. The amplitude 21 of the voltage at whichthe test was performed is tracked along one vertical axis of the map 20for each grouping of parameters or settings 23 on the DBS lead (for thisparticular depicted embodiment), while the severity of the symptomdetected or measured is displayed as a score 22 and correlated to anindicator (e.g., cross-hatching pattern, color, or the like) of eachindividual test result box 24. Again, in many preferred embodiments,rather than the labeling the groupings of parameters or settings 23 usedto provide stimulation with letters (e.g., W, X, Y, Z in the figure),they may instead be labeled by a grouping number, grouping name, or anyother labeling scheme or plan, which indicates to the clinician,physician, or technician which grouping of settings or parameters isrepresented. Preferably, the groupings are cross-referenced within thesoftware and/or GUI such that a user, clinician, physician or technicianmay readily and easily be able to see what parameters or settingscorrespond to the chosen grouping label. The right side 26 of FIG. 6portrays a new tab 27, which represents the combination of tabs A and B.This combination tab 27 represents the combination of the tuning mapsfor tasks A and B, and the combination can be of any mathematicalvariety such as averaging, weighted averaging, or the like.

The combination 27 is a result of the user selecting those two tuningmaps to be combined together and optimized in some mathematical way(e.g., averaging) in order to show the results of how the scores foreach task combine in order to optimize the DBS level for treating thesubject. In other words, the goal is to minimize the voltage at whichthe DBS is to be supplied while simultaneously minimizing the severityof the subject's symptoms and/or side effects. Combining the tuning mapsfor each task allows the user to see a resulting score and select theDBS test parameters, which are as close to optimal as possible. In apreferred embodiment, the system would be designed to be a closed-loopsystem, (i.e., for an implanted home-diagnostic and therapeutic device),which would not require extensive, or any, user input, but would performthe optimization automatically.

FIG. 7 depicts the screening process for determining whether a subjectis a good and viable candidate for DBS therapy. When a subject begins toexperience side effects 35 from medication he or she is taking to treatthe symptoms of a movement disorder, the subject or his or her clinicianmay begin to consider new treatment methods other than simply relying onmedication. The clinician may then have the patient undergo a homescreening assessment 36 to perform monitoring and recording of thesubject's symptoms and test results (motor and cognitive tests) with asystem for monitoring and recording those results. Next, preferably thesystem utilizes predictive tuning algorithms 37 to analyze the manyvariables and test results in order to make a determination as towhether the subject would benefit from DBS therapy 38. If thedetermination is that the subject would benefit, then the clinician andsubject may decide to undergo DBS surgery and therapy 38. However, ifDBS is not a viable option for the subject, then alternative therapies39 should be considered.

FIG. 8 depicts a method of the present invention utilizing an automatedand intelligent DBS (or other therapy) training system. As the subject40 performs motor and cognitive tests, as instructed via a display 42(automated), while wearing the movement disorder diagnostic device 41,the system records and analyzes the results of those tests in light ofthe many variables. The system then populates a tuning map 45, in thebackground, to show the subject's response to the tested DBS (or othertherapy) parameters for each symptom while substantially simultaneouslyentering the same data into a tuning algorithm(s). As noted herein, theaxes 43 of the optional or periodic review tuning map 45 may represent asingle test variable, or may represent a grouping of therapy settings orparameters that are used while the subject 40 conducts a movementdisorder test(s). The tuning map 45 is populated by scores 47representing the severity of the subject's 40 symptom or side effect, orsome other metric being measured, and the same data is entered into thetuning algorithm(s). The tuning map 45 also helps to map the side effectregions, as well as therapeutic and non-therapeutic regions. Aclinician, technician or physician then determines, based on the testresults, a set of therapy settings or parameters that are then enteredinto the subject's therapy (e.g., DBS) device. Alternatively, the systemmay utilize the tuning map 45 to suggest DBS parameters that willactivate the necessary therapeutic regions, avoid the side effectregions, and optimize the life of the device (i.e., battery life, etc.).The parameters are then entered into the subject's therapy device (notshown) for further testing or for delivering treatment and therapy tothe subject.

FIGS. 9A and 9B illustrate the difference between (A) monopolar and (B)bipolar DBS lead configurations and the ability to activate desiredbrain areas while avoiding others by shaping the electrical stimulationfield. While only mono- and bipolar configurations are depicted, otherconfigurations are envisioned for use with the present invention aswell. A monopolar (A) configuration provides electrical stimulation inall directions from the given contact, and that stimulation dissipatesas it radiates out from the contact. Bipolar (B) configurationssimultaneously provide electrical stimulation from 2 contacts, anddepending on the parameters used, can thus alter the shape of theelectrical stimulation field. It follows that additional contacts on asingle lead can enable more complex shaping of the stimulation field byselecting and providing stimulation from any combination of contacts ona single lead together, such as fractional control of the leads,segmented leads, steering of the electrical current, and the like. FIG.9(A) shows a monopolar configuration, which provides electricalstimulation in all directions. Thus, with a monopolar configuration, thestimulation provided activates the desired portion 56, which correspondsto the area of the subject's brain which causes occurrence of a movementdisorder symptom, but also activates a side effect region 55, whichcauses a side effect to occur. However, with a bipolar configuration, asin FIG. 9(B), the electrical field may be shaped in such a manner so asto activate the desired region 56 corresponding to a symptom and thustreat that symptom, while avoiding the side effect region 55 and thusavoid causing the side effect to occur.

Preferably, in many embodiments, the electrode leads are adapted to notonly provide or emit electrical stimulation, but also to detect, acquireor measure signals from the subject's body. In such embodiments, eachelectrode lead may comprise separate contacts for providing electricalstimulation and separate contacts for detecting, acquiring or measuring(sensing) signals from the subject's body. Preferably, the same contactson each lead are capable of performing both the emission and sensingfunctions. Multi-polar leads (leads comprising two or morecontacts—e.g., FIG. 9B) are preferable in order to enable substantiallysimultaneous acquisition or measurement of signals from the subjectconcurrent with providing electrical stimulation to the subject asneeded. While it may be possible to provide stimulation to the subjectand sense physiological or electrophysiological signals from the subjectsubstantially simultaneously from a single contact, it may be preferableto only employ each contact for a single function at any given time inorder to minimize perturbation of either the stimulation provided or thesignal(s) acquired. Given that the stimulation being provided is a knownquantity provided under known conditions, any acquired physiological orelectrophysiological signals can easily be preprocessed or processed toremove any noise caused by provided electrical stimulation, and thus thesimultaneously acquired physiological or electrophysiological signalswill effectively be unperturbed by noise or artifacts—even if the samecontact is used for both functions substantially simultaneously. Thedual-mode capability of the DBS leads/contacts in such embodiments isparticularly useful in monitoring the subject's brain function locallyas opposed to from external sensors or even implanted sensors that arelocated on the surface of the subject's brain (e.g.,electrocorticography sensors), both of which are able to provide generalbrain activity monitoring from the surface, but generally cannot resolvebeyond surface location, and certainly cannot pinpoint at the neuronbundle-level or individual neuron level. Sensing with the implanted DBSleads allows for much higher resolution brain mapping by acquiringsignals from the subject from multiple locations and depths, allowingfor much more accurate identification of brain activity throughout theentire brain, not just from the surface. Further, the dual-modefunctionality of the leads and/or contacts allows for such accuratesensing and identification of brain activity of the subject in responseto provided electrical stimulation as it is applied to the particulararea of the brain targeted so that immediate and specific feedback canbe obtained directly from the stimulated neurons and brain structures.

FIG. 10 depicts an exemplary embodiment of a device that can be carried,attached to, or otherwise readily used by the subject. The device 70 canbe any variety of interface devices, such as a cellular or smarttelephone, PDA, tablet, or the like. In the particular embodimentdepicted, the subject can view the device 70 and view, determine andselect the type of activity, action or task 78 he or she is about toperform or is performing. The activity list 78 depicts any number ofactivities, actions or tasks 78, such as activities of daily living thatthe subject may perform at various points in his or her day. When, forexample, the subject knows he or she is going to go for a walk, thesubject can merely select the walking activity, and the device 70 wouldthen communicate a set of predetermined therapy settings or parametersto program the subject's therapy device (such as an implanted DBSdevice). The therapy device would then operate under the newlyprogrammed therapy settings or parameters. The predetermined settings orparameters may be determined and programmed into the device by aclinician, physician or technician before the device is provided to thesubject. The initial and subsequent parameters or settings may also bedetermined by a clinician, physician or technician and transmitted orcommunicated remotely to the subject's DBS or therapy device. Alsoalternatively, the system may in an automated fashion and intelligentlydetermine preferred settings or parameters based on the activity, actionor task being performed, and the measurements acquired while performingsaid activity, action or task 78. This automated setting or parameterdetermination may initially be based on past performances of the electedactivity, action or task 78, but real-time measurements during eachperformance of the activity, action or task 78 may allow for real-timesetting or parameter needs to be determined and communicated from thedevice 70 to the therapy device. Thus, whenever the subject selects adesired activity, action or task 78, the device would automaticallyreprogram the subject's therapy device to provide the appropriatesettings or parameters to most effectively allow the subject to performthe elected activity, action or task 78.

Particularly in the intelligent, automated parameter or settingdetermination embodiments, the subject may be given the option to definea new activity, action or task 82. Such capability would allow thesubject to perform a new activity, action or task that he or she has notdone before, or to create a new level of a previously defined activity,action or task (such as creating a different activity, action or task 78in the activity list 74 for mowing the lawn and gardening, as opposed tojust yard work, as depicted by way of example in the figure). It may bepreferable, for some subjects, to only allow a clinician, physician ortechnician to define new activities, actions or tasks in which case thisfeature would either be disabled or removed from the interface or device70. In any event, the automated, intelligent programming systems wouldallow the device 70 to take real-time measurements of the subject'smovements, analyze the movement data, and determine the best therapyparameters or settings for maximizing the subject's ability to performthe activity, action or task. This maximization of the subject's abilityto perform the activity, action or task may correspond to a minimizationof symptoms, a minimization of side effects, a combination thereof, orany other combination of possible desired results or outcomes describedherein as they pertain to the particularly elected activity, action ortask.

Optionally, the device 70 may provide the ability to view and review thesettings for an elected activity, action or task 76. The subject or aclinician, physician or technician may simply select a button 80corresponding to the settings for a particular activity, action or task,and the therapy parameters or settings would be displayed for review.Depending on the embodiment or the person reviewing the settings, thisoption may also provide the ability to manually edit the prescribedsettings for a particular activity, action or task. Preferably, theability to edit the parameters or settings is available only to aclinician, physician or technician. The subject may be able to view thesettings in order to take notes or to discuss the settings with theclinician, physician or technician while at a remote location such as athome. In light of the various features of the device that upload andstore the parameters and settings in a database, either in real-time oron-demand, the activity settings are similarly reported and stored forremote (in time, location, or both) access.

FIG. 11 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. This particular embodiment isenvisioned to be performed in an automated fashion, by an algorithm(s),with little or no interaction required with a clinician, physician ortechnician, and where the subject is located remotely from a clinician,physician or technician, such as at home. First, a subject who has atherapy device, such as a DBS therapy device, wears a movement disorderdiagnostic device 90. The therapy device preferably has a first level oftherapy parameters or settings already programmed or entered into thedevice. The movement disorder diagnostic device is as described herein,but preferably comprises at least one physiological or movement sensorfor measuring the subject's external body motion, or some otherphysiological signal of the subject, where the sensor(s) has a signalrelated to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the subject is wearing the movement disorder diagnostic device 90,the diagnostic device then identifies or determines what, if any,activity, movement or motion the subject is performing 92. Thisidentification or determination is made based on the signal from the atleast one physiological or movement sensor of the diagnostic device. Theidentification or determination may be made by the subject who maymanually input the new activity, movement or motion into the device, bya clinician either local or remote to the subject, who may interpret thesignals from the at least one sensor and identify or determine theactivity, movement or motion, or more preferably, automatically by thedevice. Automatic identification or determination of the subject'sactivity, movement, or motion is preferably performed by a processorcontained within the device which may include a separate algorithm foractivity identification or determination, or the measurement andquantification algorithms may be able to perform this function.Preferably, even where the subject or a clinician, physician ortechnician identifies or determines and inputs the activity, movement ormotion, the device uses the signal from the at least one sensor toestimate or predict the activity, movement or motion, and allows theparticular user to confirm the identified or determined activity,movement or motion or to override the suggested identification and inputanother. The system may provide the user with several options to selectfrom as well, all based on the signals from the at least one sensor.

Once the subject's activity, movement or motion has been identified ordetermined 92, the next step is to identify or determine any motorsymptoms of a movement disorder or side effects of a treatment 94 thatthe subject is experiencing as experienced while performing theidentified or determined movement, motion or activity. Theidentification or determination of symptoms or side effects 94 issimilarly capable of being performed by either a human user orautomatically, or combination thereof. Much like the activityidentification 92 above, the subject or a clinician may input into thesystem any known symptoms or side effects. Preferably though, the systemautomatically identifies or determines the symptoms or side effectsbased at least in part on the signal from the at least one sensor, andat least in part on the identified or determined activity, movement ormotion. Again, a separate symptom and side effect identificationalgorithm may utilize the signal from the sensor and the identifiedactivity to identify or determine what symptoms and/or side effects thesubject is experiencing or has experienced. This algorithm may thenpresent options to the subject or to a clinician, again either local orremote, for confirmation or to be rejected.

Next, the step of measuring and quantifying the identified or determinedmotor symptoms or side effects 96 of the subject based at least in parton the signal of the at least one sensor(s). The movement disorderdiagnostic device uses the signal of the at least one sensor(s) toprovide an objective measurement and quantification of the severity ofthe subject's motor symptoms or side effects while the subject performsthe identified or determined activity, movement or motion. The measuredand quantified motor symptoms or side effects may include specificmovement disorder symptoms, side effects from medication and/or therapy,or combinations thereof. The trained scoring algorithms of the movementdisorder diagnostic device perform various measurements and calculationsto provide this objective quantification of the subject's motorsymptoms.

Once the subject's motor symptoms or side effects have been measured andquantified 96, data corresponding to these measured and quantified motorsymptoms is entered into a processor comprising an algorithm(s) 98 forautomated analysis. Typically, the data corresponding to the measuredand quantified motor symptoms is an objective score, as describedherein, but may be represented in numerous ways and means. Preferably,the quantified movement data is entered 98 directly and automaticallyinto the processor and into the determination algorithm(s) without theneed for any manual human intervention, such as keying in the data.

The processor and its algorithm(s) then analyze the measured andquantified movement data and calculate a second level of therapyparameters or settings 100. This second level of parameters or settingspreferably corresponds to a mode of therapy or treatment that addressesthe subject's needs as determined based on the identified or determinedactivity and symptoms or side effects, and the measured and quantifiedmotor symptom data, as well as other data, goals, or objectives. Inother words, if the system determines that, for example, the subject isexperiencing a very strong tremor while driving, such determinationbeing made as a result of the identification of the subject's activityand symptoms as well as measurement of the subject's movement andquantifying the severity of the tremor, the processor and algorithmwould provide a second level of parameters or settings 100 that wouldreduce or minimize the tremor the subject is experiencing. As noted, thecalculation of a second level of parameters or settings may be based onany number of constraints or desired results for the subject, not solelythe immediate symptom or side effect the subject is experiencing. Forexample, if the subject's main concern is reducing or minimizing symptomoccurrence and or severity, the processor and its algorithms will takethis desired goal into account when calculating the second level ofparameters or settings. Similarly, the calculation of settings orparameters may be based on a desired reduction or minimization of sideeffects from medication or the therapy. Also, the calculation may bemade to balance multiple desired results, such as if a slightly higherrate of occurrence of symptoms is acceptable to the subject in exchangefor a minimization of side effects. Other examples of desired resultsthat may be used to determine the second level of therapy parameters orsettings for all embodiments include, but are not limited to, atherapeutic window (in terms of time or some other factor) in which thesubject most positively responds to therapy, battery life, and othersuch constraints that might be considered in terms of optimizing thetherapy parameters or settings. In any determination, the subject andthe clinician, physician or technician decide what the initial desiredresult is, and these desired results, goals, or constraints areprogrammed into the processor and its algorithm(s) for the decisionmaking process. In some embodiments, the desired result, goal orconstraints may be edited, either by a clinician, physician ortechnician, or by the subject, in order to allow the algorithm to mostaccurately analyze the data in light of the optimal treatment for thesubject.

Once this second level of parameters or settings has been calculated bythe processor and its algorithm(s) 100, the parameters or settings arethen transmitted to the subject's therapy device 102 (e.g., DBS device).The therapy device preferably comprises at least one electroniccomponent for receiving such signals, and uses this at least onecomponent to receive a signal(s) comprising the second level of therapyparameters or settings from the diagnostic device. The parameters orsettings may additionally transmitted via wireless communication, asdescribed herein, between the subject's therapy device and a remotelocation such as to a database or server for storage, or directly to aremote clinician physician or technician for optional review. Once thetherapy device receives the transmitted 102 second level of therapyparameters or settings, the second level of parameters or settings isthen entered in to the subject's therapy device 104 for the device toprovide therapy according to those parameters or settings. As such, thenew, second level of parameters or settings is programmed into thesubject's therapy device, and the device then operates according tothose new parameters or settings 104 and provides that newly determinedcourse of therapy or treatment to the subject.

FIG. 12 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. This particular embodiment isenvisioned to be performed in an automated fashion, by an algorithm(s),with little or no interaction required with a clinician, physician ortechnician, and where the subject is located remotely from a clinician,physician or technician, such as at home. First, a subject who has atherapy device, such as a DBS therapy device, wears a movement disorderdiagnostic device 90. The therapy device preferably has a first level oftherapy parameters or settings already programmed or entered into thedevice. The movement disorder diagnostic device is as described herein,but preferably comprises at least one physiological or movement sensorfor measuring the subject's external body motion, or some otherphysiological signal of the subject, where the sensor(s) has a signalrelated to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the subject is wearing the movement disorder diagnostic device 90,the diagnostic device then identifies or determines what, if any,activity, movement or motion the subject is performing 92. Thisidentification or determination is made based on the signal from the atleast one physiological or movement sensor of the diagnostic device. Theidentification or determination may be made by the subject who maymanually input the new activity, movement or motion into the device, bya clinician either local or remote to the subject, who may interpret thesignals from the at least one sensor and identify or determine theactivity, movement or motion, or more preferably, automatically by thedevice. Automatic identification or determination of the subject'sactivity, movement, or motion is preferably performed by a processorcontained within the device which may include a separate algorithm foractivity identification or determination, or the measurement andquantification algorithms may be able to perform this function.Preferably, even where the subject or a clinician, physician ortechnician identifies or determines and inputs the activity, movement ormotion, the device uses the signal from the at least one sensor toestimate or predict the activity, movement or motion, and allows theparticular user to confirm the identified or determined activity,movement or motion or to override the suggested identification and inputanother. The system may provide the user with several options to selectfrom as well, all based on the signals from the at least one sensor.

Once the subject's activity, movement or motion has been identified ordetermined 92, the next step is to identify or determine any motorsymptoms of a movement disorder or side effects of a treatment 94 thatthe subject is experiencing as experienced while performing theidentified or determined movement, motion or activity. Theidentification or determination of symptoms or side effects 94 issimilarly capable of being performed by either a human user orautomatically, or combination thereof. Much like the activityidentification 92 above, the subject or a clinician may input into thesystem any known symptoms or side effects. Preferably though, the systemautomatically identifies or determines the symptoms or side effectsbased at least in part on the signal from the at least one sensor, andat least in part on the identified or determined activity, movement ormotion. Again, a separate symptom and side effect identificationalgorithm may utilize the signal from the sensor and the identifiedactivity to identify or determine what symptoms and/or side effects thesubject is experiencing or has experienced. This algorithm may thenpresent options to the subject or to a clinician, again either local orremote, for confirmation or to be rejected.

Next, the step of measuring and quantifying the identified or determinedmotor symptoms or side effects 96 of the subject based at least in parton the signal of the at least one sensor(s). The movement disorderdiagnostic device uses the signal of the at least one sensor(s) toprovide an objective measurement and quantification of the severity ofthe subject's motor symptoms or side effects while the subject performsthe identified or determined activity, movement or motion. The measuredand quantified motor symptoms or side effects may include specificmovement disorder symptoms, side effects from medication and/or therapy,or combinations thereof. The trained scoring algorithms of the movementdisorder diagnostic device perform various measurements and calculationsto provide this objective quantification of the subject's motorsymptoms.

Once the subject's motor symptoms or side effects have been measured andquantified 96, data corresponding to these measured and quantified motorsymptoms is entered into a processor comprising an algorithm(s) 98 forautomated analysis. Typically, the data corresponding to the measuredand quantified motor symptoms is an objective score, as describedherein, but may be represented in numerous ways and means. Preferably,the quantified movement data is entered 98 directly and automaticallyinto the processor and into the determination algorithm(s) without theneed for any manual human intervention, such as keying in the data.

The processor and its algorithm(s) then analyze the measured andquantified movement data and calculate at least two optional groups oftherapy parameters or settings 106. These optional of parameters orsettings each preferably correspond to a mode of therapy or treatmentthat addresses the subject's needs as determined based on the identifiedor determined activity and symptoms or side effects, and the measuredand quantified motor symptom data, as well as other data, goals, orobjectives. More specifically, each optional group of parameters orsettings preferably corresponds to a different and separate motorsymptom or side effect identified above. In other words, if the systemdetermines that, for example, the subject is experiencing a tremor andincreased rigidity while sleeping, such determination being made as aresult of the identification of the subject's activity and symptoms aswell as measurement of the subject's movement and quantifying theseverity of the tremor and rigidity, the processor and algorithm wouldprovide at least two optional groups of parameters or settings: at leastone that would reduce or minimize the tremor the subject isexperiencing, and at least one that would ease or reduce the rigidity.As noted, the calculation of optional groups of parameters or settingsmay be based on any number of constraints or desired results for thesubject, not solely the immediate symptom or side effect the subject isexperiencing. For example, if the subject's main concern is reducing orminimizing symptom occurrence and or severity, the processor and itsalgorithms will take this desired goal into account when calculating theoptional groups of parameters or settings. Similarly, the calculation ofsettings or parameters may be based on a desired reduction orminimization of side effects from medication or the therapy. Also, thecalculation may be made to balance multiple desired results, such as ifa slightly higher rate of occurrence of symptoms is acceptable to thesubject in exchange for a minimization of side effects. Other examplesof desired results that may be used to determine the second level oftherapy parameters or settings for all embodiments include, but are notlimited to, a therapeutic window (in terms of time or some other factor)in which the subject most positively responds to therapy, battery life,and other such constraints that might be considered in terms ofoptimizing the therapy parameters or settings. In any determination, thesubject and the clinician, physician or technician decide what theinitial desired result is, and these desired results, goals, orconstraints are programmed into the processor and its algorithm(s) forthe decision making process. In some embodiments, the desired result,goal or constraints may be edited, either by a clinician, physician ortechnician, or by the subject, in order to allow the algorithm to mostaccurately analyze the data in light of the optimal treatment for thesubject.

Once the at least two optional groups of therapy parameters or settingshas been calculated 106, the next step is to select at least one of thegroups 108 to be used by the therapy device. In the particularlydepicted embodiment, the subject selects at least one of the groups tobe used; however, the selection of at least one optional group mayalternatively be made by a clinician, physician, technician or otheruser, or automatically by the system. Where the subject selects theoptional group(s) to be used, such as depicted, preferably the groupsare displayed or otherwise communicated to the subject directly via thedevice. The options may be portrayed on a visual display, may becommunicated to the subject's smartphone, personal computer, or othersuch device, presented audibly, or by any other similar method forpresenting the options to the subject. Preferably, the optional groupsare presented to the subject in a manner that is simple and easy for himor her, presumably a layperson, to understand, and not as a list ofcomplex parameters or settings that a layperson would not be qualifiedto interpret and select for purposes of medical treatment. By way ofnon-limiting example, the groups can be presented to the subject interms of the identified or determined activity, movement or motion thesubject may be performing, or the identified or determined symptom(s) orside effect(s) he or she may be experiencing, thus allowing the subjectto select the group that would best meet his or her needs for theparticular activity, symptom or side effect. Other means of presentingthe groups for easy layperson subject selection are contemplated aswell. For embodiments where the clinician, physician or technicianselects at least one optional group, preferably the groups aretransmitted to the clinician at a remote location, along with at leastone, though preferably all of the identified or determined activity,movement or motion, identified or determined symptom(s) and/or sideeffect(s), as well as the data corresponding to the measured andquantified motor symptoms and/or side effects. The clinician can thenanalyze the full spectrum of information and determine which group isthe best option for the subject using the identified items, the measuredand quantified data, and the proposed groups. The clinician, physicianor technician then further has the optional ability to edit any of theoptional groups, or create an entirely new group. Alternatively, thesystem can be completely automated, such as a closed-loop therapysystem, whereby the system determines which of the calculated optionalgroups is optimal in light of the identified or determined factorsincluding activity, movement or motion and symptom(s) and/or sideeffect(s). In such automated systems, all calculation and selection maybe internal and substantially in real-time, with no need to display ortransmit options or data. As such, the selected optional group may morerapidly be implemented by the therapy device and more rapidly providethe beneficial therapy to the subject.

Once the optional group(s) of parameters or settings has been calculatedby the processor and its algorithm(s) 106 and selected 108, the selectedoptional group of parameters or settings is then transmitted to thesubject's therapy device 110 (e.g., DBS device). The therapy devicepreferably comprises at least one electronic component for receivingsuch signals, and uses this at least one component to receive asignal(s) comprising the selected optional group(s) of therapyparameters or settings from the diagnostic device, or from anotherprogramming device such as in the possession of the clinician, physicianor technician. The parameters or settings may additionally transmittedvia wireless communication, as described herein, between the subject'stherapy device and a remote location such as to a database or server forstorage, or directly to a remote clinician physician or technician foroptional review. Once the therapy device receives the transmitted 110selected optional group(s) of therapy parameters or settings, theselection optional group(s) of parameters or settings is then entered into the subject's therapy device 112 for the device to provide therapyaccording to those parameters or settings. As such, the new, selectedoptional group of parameters or settings is programmed into thesubject's therapy device, and the device then operates according tothose new parameters or settings 112 and provides that newly determinedcourse of therapy or treatment to the subject.

FIG. 13 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. This particular embodiment isenvisioned to be performed in an automated fashion, by an algorithm(s),with little or no interaction required with a clinician, physician ortechnician, and where the subject is located remotely from a clinician,physician or technician, such as at home. First, a subject who has atherapy device, such as a DBS therapy device, wears a movement disorderdiagnostic device 90. The therapy device preferably has a first level oftherapy parameters or settings already programmed or entered into thedevice. The movement disorder diagnostic device is as described herein,but preferably comprises at least one physiological or movement sensorfor measuring the subject's external body motion, or some otherphysiological signal of the subject, where the sensor(s) has a signalrelated to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the subject is wearing the movement disorder diagnostic device 90,the diagnostic device then identifies or determines what, if any,activity, movement or motion the subject is performing 92. Thisidentification or determination is made based on the signal from the atleast one physiological or movement sensor of the diagnostic device. Theidentification or determination may be made by the subject who maymanually input the new activity, movement or motion into the device, bya clinician either local or remote to the subject, who may interpret thesignals from the at least one sensor and identify or determine theactivity, movement or motion, or more preferably, automatically by thedevice. Automatic identification or determination of the subject'sactivity, movement, or motion is preferably performed by a processorcontained within the device which may include a separate algorithm foractivity identification or determination, or the measurement andquantification algorithms may be able to perform this function.Preferably, even where the subject or a clinician, physician ortechnician identifies or determines and inputs the activity, movement ormotion, the device uses the signal from the at least one sensor toestimate or predict the activity, movement or motion, and allows theparticular user to confirm the identified or determined activity,movement or motion or to override the suggested identification and inputanother. The system may provide the user with several options to selectfrom as well, all based on the signals from the at least one sensor.

Once the subject's activity, movement or motion has been identified ordetermined 92, the next step is to identify or determine any motorsymptoms of a movement disorder or side effects of a treatment 94 thatthe subject is experiencing as experienced while performing theidentified or determined movement, motion or activity. Theidentification or determination of symptoms or side effects 94 issimilarly capable of being performed by either a human user orautomatically, or combination thereof. Much like the activityidentification 92 above, the subject or a clinician may input into thesystem any known symptoms or side effects. Preferably though, the systemautomatically identifies or determines the symptoms or side effectsbased at least in part on the signal from the at least one sensor, andat least in part on the identified or determined activity, movement ormotion. Again, a separate symptom and side effect identificationalgorithm may utilize the signal from the sensor and the identifiedactivity to identify or determine what symptoms and/or side effects thesubject is experiencing or has experienced. This algorithm may thenpresent options to the subject or to a clinician, again either local orremote, for confirmation or to be rejected.

Next, the step of measuring and quantifying the identified or determinedmotor symptoms or side effects 96 of the subject based at least in parton the signal of the at least one sensor(s). The movement disorderdiagnostic device uses the signal of the at least one sensor(s) toprovide an objective measurement and quantification of the severity ofthe subject's motor symptoms or side effects while the subject performsthe identified or determined activity, movement or motion. The measuredand quantified motor symptoms or side effects may include specificmovement disorder symptoms, side effects from medication and/or therapy,or combinations thereof. The trained scoring algorithms of the movementdisorder diagnostic device perform various measurements and calculationsto provide this objective quantification of the subject's motorsymptoms.

Once the subject's motor symptoms or side effects have been measured andquantified 96, data corresponding to these measured and quantified motorsymptoms is entered into a processor comprising an algorithm(s) 98 forautomated analysis. Typically, the data corresponding to the measuredand quantified motor symptoms is an objective score, as describedherein, but may be represented in numerous ways and means. Preferably,the quantified movement data is entered 98 directly and automaticallyinto the processor and into the determination algorithm(s) without theneed for any manual human intervention, such as keying in the data.

The processor and its algorithm(s) then analyze the measured andquantified movement data and calculate a second level of therapyparameters or settings 100. This second level of parameters or settingspreferably corresponds to a mode of therapy or treatment that addressesthe subject's needs as determined based on the identified or determinedactivity and symptoms or side effects, and the measured and quantifiedmotor symptom data, as well as other data, goals, or objectives. Inother words, if the system determines that, for example, the subject isexperiencing a very strong tremor while driving, such determinationbeing made as a result of the identification of the subject's activityand symptoms as well as measurement of the subject's movement andquantifying the severity of the tremor, the processor and algorithmwould provide a second level of parameters or settings 100 that wouldreduce or minimize the tremor the subject is experiencing. As noted, thecalculation of a second level of parameters or settings may be based onany number of constraints or desired results for the subject, not solelythe immediate symptom or side effect the subject is experiencing. Forexample, if the subject's main concern is reducing or minimizing symptomoccurrence and or severity, the processor and its algorithms will takethis desired goal into account when calculating the second level ofparameters or settings. Similarly, the calculation of settings orparameters may be based on a desired reduction or minimization of sideeffects from medication or the therapy. Also, the calculation may bemade to balance multiple desired results, such as if a slightly higherrate of occurrence of symptoms is acceptable to the subject in exchangefor a minimization of side effects. Other examples of desired resultsthat may be used to determine the second level of therapy parameters orsettings for all embodiments include, but are not limited to, atherapeutic window (in terms of time or some other factor) in which thesubject most positively responds to therapy, battery life, and othersuch constraints that might be considered in terms of optimizing thetherapy parameters or settings. In any determination, the subject andthe clinician, physician or technician decide what the initial desiredresult is, and these desired results, goals, or constraints areprogrammed into the processor and its algorithm(s) for the decisionmaking process. In some embodiments, the desired result, goal orconstraints may be edited, either by a clinician, physician ortechnician, or by the subject, in order to allow the algorithm to mostaccurately analyze the data in light of the optimal treatment for thesubject.

Once this second level of parameters or settings has been calculated bythe processor and its algorithm(s) 100, the parameters or settings arethen transmitted to the subject's therapy device 102 (e.g., DBS device).The therapy device preferably comprises at least one electroniccomponent for receiving such signals, and uses this at least onecomponent to receive a signal(s) comprising the second level of therapyparameters or settings from the diagnostic device. The parameters orsettings may additionally transmitted via wireless communication, asdescribed herein, between the subject's therapy device and a remotelocation such as to a database or server for storage, or directly to aremote clinician physician or technician for optional review. Once thetherapy device receives the transmitted 102 second level of therapyparameters or settings, the second level of parameters or settings isthen entered in to the subject's therapy device 104 for the device toprovide therapy according to those parameters or settings. In thepresent embodiment, the second level of therapy parameters or settingsis an optimized group of settings that is calculated to address each ofthe identified or determined symptoms and side effects to at least somedegree. Optimization preferably takes into account the identified ordetermined activity, movement or motion as well as the identified ordetermined symptoms and side effects to calculate a second level oftherapy parameters or settings that provides the subject with as muchrelief from each of the symptoms and side effects as possible, whilemaximizing the subject's ability to perform the activity, movement ormotion with the greatest degree of ability, comfort and safety. As such,the new, second level of parameters or settings is programmed into thesubject's therapy device, and the device then operates according tothose new parameters or settings 104 and provides that newly determinedcourse of therapy or treatment to the subject.

FIG. 14 is a flow chart depicting one embodiment of a process by whichthe tuning algorithm(s) is used to determine therapy parameters orsettings and program those settings into a subject's therapy device.Like the embodiments described above, data corresponding to measured andquantified motor symptoms is entered into a processor with tuningalgorithm(s) 130 for automated analysis. Typically, the datacorresponding to the measured and quantified motor symptoms is anobjective score, as described herein, but may be represented in numerousways and means, and may additionally contain information and/or datacorresponding to the identified or determined activity, movement ormotion and motor symptom(s) and/or side effect(s). Preferably, thequantified movement data is entered directly and automatically into theprocessor and its determination algorithm(s) 130 without the need forany manual human intervention, such as keying in the data.

The processor and its determination algorithm(s) then analyzes theidentified or determined data and the measured and quantified movementdata and calculates a second level of therapy parameters or settings132. This second level of parameters or settings preferably correspondsto a mode of therapy or treatment that addresses the subject's needs asdetermined based on the measured and quantified motor symptom data, aswell as other data, goals, or objectives. In other words, if the systemdetermines that the subject is experiencing a very strong tremor, suchdetermination being made as a result of the identified activity andsymptoms/side effects and measurement of the subject's movement andquantifying the severity of the tremor, the processor and algorithmwould provide a second level of parameters or settings 132 that wouldreduce or minimize the tremor the subject is experiencing. As noted, thecalculation of a second level of parameters or settings may be based onany number of constraints or desired results for the subject, not solelythe identified symptom(s) or side effect(s) the subject is experiencing.Also, the calculation may be made to balance multiple desired results,such as if a slightly higher rate of occurrence of symptoms isacceptable to the subject in exchange for a minimization of sideeffects. Other examples of desired results that may be used to calculatethe second level of therapy parameters or settings for all embodimentsinclude, but are not limited to, a therapeutic window (in terms of timeor some other factor) in which the subject most positively responds totherapy, battery life, and other such constraints that might beconsidered in terms of optimizing the therapy parameters or settings. Inany determination, the subject and the clinician, physician ortechnician decide what the initial desired result is, and these desiredresults, goals, or constraints are programmed into the algorithm for thedecision making process. In some embodiments, the desired result, goalor constraints may be edited, either by a clinician, physician ortechnician, or by the subject, in order to allow the algorithm to mostaccurately analyze the data in light of the optimal treatment for thesubject.

In the depicted embodiment, the second level of therapy parameters orsettings is then transmitted to a clinician at a remote location, andoutput or displayed for review 134 prior to implementation. Once thesecond level (or selected group, or selected and combined group) hasbeen transmitted and presented to the clinician, the clinician cananalyze the algorithm-generated settings to ensure they are withinacceptable safety limits, as well as ensuring that they do in factaddress the needs of the subject. Preferably, the transmission of thesecond settings is performed wirelessly and securely, particularly wherethe subject is located remotely from the clinician, physician ortechnician. The parameters or settings are preferably displayed visuallyto the clinician, physician or technician, such as on a monitor ordisplay device. The parameters or settings may be displayed in anyformat known to those skilled in the art, including, but not limited toa textual report such as in an email or text document sent to the careprovider, transmitted to a software package that displays the parametersor settings in a particular graphical user interface, or transmitted toa centralized or cloud-based database where the clinician, physician ortechnician can access them for review. Where the parameters or settingsare viewed in a software package, the present invention is intended tobe adaptable or formattable such that the parameter or settings reportor transmission may be used in any commercially available package, orthe like.

When the clinician, physician or technician reviews the parameters orsettings, he or she then has the option of approving or rejecting theparameters or settings 136. The decision to approve or deny ispreferably based on the likelihood that the algorithm(s)′ providedparameters or settings will achieve the subject's desired outcome orgoal, and any other constraints that have been elected either by thesubject, or by the clinician, physician or technician in conjunctionwith the subject. If the clinician, physician or technician determinesthat the parameters or settings will not meet the desired results, goalsor constraints, then the settings or parameters can be rejected 138,this rejection is communicated or transmitted back to the subject'sdiagnostic device, and the determination algorithm(s) repeats theprocess of using the measured and quantified motor symptom data toprovide another set of therapy parameters or settings 132. New sensorrecordings, identifications of activity, symptoms and/or side effectsmay also be made once the parameters or settings have been rejected.This process may be repeated iteratively until acceptable parameters orsettings are achieved. Optionally, the clinician, physician ortechnician may be given the ability to suggest starting parameters forthe algorithm to begin with, thus circumventing the need for furthermotor symptom measurement and quantification. When the algorithm(s) aretriggered to provide another iteration of parameters or settings, theabove steps are repeated until the parameters or settings meet orachieve the desired end result for therapy.

When the clinician determines that the parameters or settings are, infact, likely to meet those goals, then he or she approves the parametersor settings 140, and the second level, selected group or combinedselected group of parameters or settings is transmitted from theclinician at a remote location back to the subject's therapy device ordiagnostic device, and entered automatically and wirelessly into thesubject's therapy device 142 in the same or similar manner as describedherein. As such, the new, selected group of parameters or settings isprogrammed into the subject's therapy device, and the device thenoperates according to those new parameters or settings 144 and providesthat newly determined course of therapy or treatment to the subject.

FIG. 15 depicts an operating embodiment of the present inventionbeginning with the initial occurrence of movement disorder symptoms andending with continuing monitoring and treatment or therapy. The depictedembodiment describes a system involving continuous home monitoring suchthat the device operates virtually full-time, monitoring, measuring andanalyzing the subject's movement data continually; however, alternativeembodiments exist that operate similarly, but with part-time oron-demand monitoring, measuring and analysis. In either embodiment, thesubject initially exhibits symptoms of a movement disorder and attendsan appointment with a clinician 160. At the appointment, the clinicianexamines the subject 162, and upon analysis, diagnoses the subject ashaving a movement disorder, and subsequently orders a course oftreatment or therapy 164. At a follow-up visit, the subject may reportthat symptoms fluctuate greatly throughout the day 166, even while onthe prescribed treatment or therapy plan. The clinician then decides toperform in-home continual testing 168 to better determine the severityof the subject's symptoms. Continuous home monitoring 170 begins withthe initial programming 172 of any movement monitoring devices orautomated treatment delivery devices for the subject, or instructing thesubject how to do so. This initial programming may be performedin-clinic or remotely, and may be performed manually or integrated withthe review of a clinician, physician or technician, or may be performedintelligently in an automated or semi-automated process utilizingtrained tuning algorithms. The device, containing at least one sensor,preferably an accelerometer and/or gyroscope of at least three axes, butoptionally another sensor capable of measuring motion, such as an EMG,continually records the subject's movement during activities of dailyliving 174. In addition, the device can include two or more types ofsensors, preferably accelerometers and gyroscopes. Activities of dailyliving may include folding laundry, handwriting, eating, dressing,self-care, walking, running, and the like. Optionally, the clinician mayorder the subject to perform clinical tasks such as finger tapping, nosetouching, or the like, as defined by standardized scales such as theUPDRS, TRS, and the like, at regularly scheduled periods. Such movementdata would also be continually recorded.

A trained tuning algorithm, preferably incorporated by at least onecomputer processor, analyzes the recorded movement data 176. This dataanalysis may be performed at a scheduled time where the data is uploadedto the algorithm and analyzed, or, more preferably, may be performed inreal time. The algorithm and processor function to distinguish voluntarymotion of activities of daily living or clinician ordered tasks frommovement disorder symptoms and quantify their severity. Preferably thetrained algorithms and computer processor are also in two-waycommunication 178 with a central database 180 or multiple databases madeup of previous patient movement data, disorder histories, treatmenthistories, and the like. Preferably two or more databases are used forreading. Such a database 180 would preferably retain information fromthe current subject for use with future subjects 182 (maintainingsubject privacy and confidentiality at all times) and work with thetrained algorithms and processor to determine a recommended treatmentfor the current subject based on the previous patient data. Thisdatabase 180 could optionally be used as a real-time gateway forproviding updates to the subject's clinician 184 regarding the subject'sstatus.

If the trained algorithms and processor determine 176 that the patientstill suffers from movement disorder symptoms 186, a new course oftreatment or therapy is determined 188 either based solely on thesubject's measured and quantified symptoms, in conjunction with thecentral database 180 as previously described, or a combination of thetwo. If the subject has an automated treatment delivery device, it ispreferably reprogramed according to the new treatment protocol 190.Preferably, this reprogramming of the subject's device is performedremotely, and in an automated, intelligent fashion requiring little, ormore preferably no interaction from a clinician, physician ortechnician. The movement measuring device then continues to record newmovement data and the process repeats. If the trained algorithms andprocessor determine 176 movement disorder symptoms no longer persist 192then no new treatment is needed, no changes are made 194, and the devicecontinues recording movement data.

FIG. 16 is a flow chart depicting one example of a tuning algorithm usedto determine the therapy parameters or settings that can be programmedinto a subject's therapy device for another iteration of testing or forproviding therapy according to those parameters or settings. Thisparticularly depicted embodiment is merely an example, and many othercombinations of parameters or settings, number of variables and/or stepsare envisioned. First, a set of initial parameters 200 is programmedinto the subject's therapy device. These initial parameters may bepre-programmed, programmed manually or as part of an integrated system,or automatically programmed via an intelligent algorithm. Further, theinitial parameters may define any number of variables or parameters orsettings as disclosed herein to be set while others are altered ormodified through the tuning process. In the depicted embodiment, someinitial parameters or settings include a pulse width (PW) of 90 μs,frequency (F) of 130 Hz, and pulse amplitude (PA) of 0 mA. An amplitudeof 0 mA essentially means that no therapeutic current is being provided,or the therapy is turned off, but is provided as an initial setting tobeing the testing process from which the amplitude is increasedgradually throughout the testing iterations. Once these parameters areprogrammed into the subject's therapy device such that the device canprovide therapy according to these initial parameters or settings, thetuning process may begin by initially increasing the pulse amplitude 202to a first test level provided to the subject, in the figure shown to bean increase of 0.25 mA. As the therapy is provided to the subjectaccording to the initial parameters and the first level of testparameters, the movement disorder diagnostic device (not shown) measuresand quantifies the subject's movement (not shown) in order to determinethe level of symptoms, side effects, and the like that the subjectexperiences while receiving therapy according to the provided parametersor settings. Based on the measured and quantified movement data, thedepicted algorithm first determines whether side effects are occurring204. If side effects occur under the provided therapy parameters orsettings, then the algorithm may determine that using the presentlytested contact may result in persistent side effects, and move on to thenext contact 218 to test and determine whether therapy can be providedin an alternative pattern from the different contacts to avoid the sideeffects.

If side effects do not occur or do not persist from one iteration of thetest to the next, then the algorithm then determines whether thesubject's symptoms have improved 206 as a result of the tested therapyparameters or settings. This determination, too, is based on themeasured and quantified movement data provided by the movement disorderdiagnostic device. If the algorithm determines that the symptoms havenot improved based on the provided therapy parameters or settings, itmay next perform a query to see how many individual parameters orsettings have been tested (i.e., changed individually to determine theparticular parameter's effect on the subject's side effects and/orsymptoms), or how many groups of parameters or settings have been tested214. In the depicted embodiment, the threshold value is eightparameters/settings or groups thereof. Therefore, in the depictedembodiment, if eight parameters/settings or groups thereof have beentested through the depicted process, the algorithm determines whetherthere has been any improvement in the last four changes inparameters/settings or groups 216. If there has been no suchimprovement, then again, the algorithm may move on to the next contact218 in order to try and achieve a therapeutic response from anothercontact that may address the subject's symptoms and/or side effects andother constraints.

If, however, the depicted algorithm determines that a) the subject'ssymptoms did improve under the provided therapy parameters or settings206; b) symptoms did not improve and fewer than eightparameters/settings or groups thereof have been tested 214; or c) atleast eight parameters/settings or group have been tested, but there hasbeen some improvement within the last four iterations 216, then thealgorithm next determines whether the therapy parameters or settings arebeing provided at a maximum value for one of those parameters orsettings 208—in the depicted case pulse amplitude. Pre-determinedparameter or settings limits may be defined to keep the therapy deviceoperating within safe limits in order to protect the subject. If thespecific parameter or setting that is being tested (in the depictedcase, pulse amplitude) has not reached its maximum value, then thealgorithm may again increase the value of that parameter or setting 202and repeat the process. If the maximum value has already been reachedfor the particular parameter or setting, then that variable cannot beincreased any further, and the algorithm determines whether anotherindividual parameter or setting is at its maximum level 210—in thedepicted case frequency. If the frequency has not reached its maximumvalue yet, then the algorithm reduces the amplitude to zero, increasesthe frequency 220 and then again begins the iterative process byinitially increasing the amplitude 202 to provide therapy to the subjectat the new levels of parameters or settings.

If, however, symptoms have shown improvement as a result in the changein therapy parameters or settings, and both of the first two parametersor settings have reached their maximum levels, then the algorithm nextdetermines if yet another parameter or setting (in the depicted case,pulse width) has yet reached its maximum value 212. If all of theparameters or settings desired to be tested have reached their maximums,then the algorithm determines that the tested contact, though close, maynot provide the best course of therapy, and moves on to the next contact218 to begin the process over. If, however, the next parameter orsetting 212 has not reached its maximum value, the algorithm againreduces the amplitude to zero, maintains the maximum frequency, andincreases the pulse width 222 (again, these are exemplary parameters orsettings, and other combinations are envisioned). Once the updatedparameters or settings have been determined, the algorithm again beginsthe process over by slightly increasing the amplitude 202 to provide atherapeutic current according to the new settings, and repeats thetesting process. This decision process is repeated by the intelligentalgorithm until it determines that the best combination of contact(s)and parameters or settings has been achieved, resulting in an optimizedtherapy that takes into account the subject's side effects, symptoms,and/or other constraints.

FIG. 17 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. First, a movement disorderdiagnostic device is provided to a subject 270 who has a therapy device,such as a DBS therapy device. The movement disorder diagnostic device isas described herein, but preferably comprises at least one physiologicalor movement sensor for measuring the subject's external body motion, orsome other physiological signal of the subject, where the sensor(s) hasa signal related to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the movement disorder diagnostic device has been provided 270 tothe subject, and the subject has donned or attached the device, the nextstep is to instruct the subject 272 to perform at least one movementdisorder test(s) while the subject is undergoing therapy from thetherapy (e.g., DBS) device, or is under the effects of recentlyadministered therapy therefrom. These instructions may include a list ofwhich test(s) the subject is to perform, directions on how to performthe test, or a combination of both. The instructions to perform a testor tests may be given 272 in person (if in a clinical setting) by aclinician, physician or technician, or more preferably may be providedin an automated or electronic fashion. For example, the instruction toperform the test(s) may be provided in an automated fashion to thesubject via a video display, or a notification or alert message providedvia such a display or perhaps the subject's smart phone, on a displaydevice via tele- or videoconference with a clinician, physician ortechnician, or the like. The instructions are provided 272, eitheraudibly, visually, or a combination thereof. The subject's performanceof the tasks is thus affected by the therapy being provided, or recentlyprovided by the therapy device.

While the subject is performing the at least one movement disordertest(s) as instructed 272, the step of measuring and quantifying motorsymptoms 274 of the subject based at least in part on the signal of theat least one sensor(s) is performed. The movement disorder diagnosticdevice uses the signal of the at least one sensor(s) to provide anobjective measurement and quantification of the severity of thesubject's motor symptoms while the subject performs the at least onemovement disorder test. The measured and quantified motor symptoms mayinclude specific movement disorder symptoms, side effects frommedication and/or therapy, or combinations thereof. The trained scoringalgorithms of the movement disorder diagnostic device perform variousmeasurements and calculations to provide this objective quantificationof the subject's motor symptoms.

Once the subject's motor symptoms have been measured and quantified 274,data corresponding to these measured and quantified motor symptoms istransmitted to a remote location 276. Typically, the data correspondingto the measured and quantified motor symptoms is an objective score, asdescribed herein, but may be represented in numerous ways and means.Preferably, the data is transmitted 276 directly from the subject'smovement disorder diagnostic device using at least on electricalcomponent for sending or transmitting signals. Preferably, suchtransmission is performed wirelessly as described herein, though it maybe performed by use of a tethered or docking station system where thediagnostic device is placed in contact with the tethered communicationssystem or docking station which then transmits the data. As describedherein, the data is preferably transmitted directly to a remote locationwhere a clinician, physician or technician can access the dataimmediately or at will for analysis and review. Additionally oralternatively, the data may be transmitted to a form of data storagesuch as a centralized server, cloud-based server, or other storagedatabase. The clinician, physician or technician can then either accessthe data directly from a computer device to which the data istransmitted 276 or from the storage system in order to review andanalyze the data. Using this data, the clinician, physician ortechnician then determines a second level of therapy (e.g., DBS)parameters or settings 278 based on the data and with the goal ofimproving the subject's movement in a manner as described herein. Thissecond level of parameters or settings preferably corresponds to a modeof therapy or treatment that addresses the subject's needs as determinedbased on the measured and quantified motor symptom data, as well asother data, goals, or objectives. In other words, if the clinician orsystem determines that the subject is experiencing a very strong tremor,such determination being made as a result of the measurement of thesubject's movement and quantifying the severity of the tremor, thesecond level of parameters or settings 278 would aim to reduce orminimize the tremor the subject is experiencing. As noted, thedetermination of a second level of parameters or settings may be basedon any number of constraints or desired results for the subject, notsolely the immediate symptom or side effect the subject is experiencing.For example, if the subject's main concern is reducing or minimizingsymptom occurrence and or severity, the clinician, physician ortechnician, or algorithm will take this desired goal into account whendetermining the second level of parameters or settings. Similarly, thedetermination of settings or parameters may be based on a desiredreduction or minimization of side effects from medication or thetherapy. Also, the determination may be made to balance multiple desiredresults, such as if a slightly higher rate of occurrence of symptoms isacceptable to the subject in exchange for a minimization of sideeffects. Other examples of desired results that may be used to determinethe second level of therapy parameters or settings for all embodimentsinclude, but are not limited to, a therapeutic window (in terms of timeor some other factor) in which the subject most positively responds totherapy, battery life, and other such constraints that might beconsidered in terms of optimizing the therapy parameters or settings. Inany determination, the subject and the clinician, physician ortechnician decide what the initial desired result is, and these desiredresults, goals, or constraints are programmed into the algorithm for thedecision making process. In some embodiments, the desired result, goalor constraints may be edited or changed in order to allow the secondlevel of parameters to provide optimal treatment for the subject.

Once the second level of therapy parameters or settings has beendetermined or decided upon, this second level of parameters or settingsis then transmitted to the subject's therapy device 279 (e.g., DBSdevice). The therapy device preferably comprises at least one electroniccomponent for receiving such signals, and uses this at least onecomponent to receive a signal(s) comprising the second level of therapyparameters or settings. The parameters or settings are preferablytransmitted 279 via wireless communication, as described herein, betweenthe remote location and the subject's therapy device. Once the therapydevice receives the transmitted second level of therapy parameters orsettings, the second level of parameters or settings is then entered into the subject's therapy device 280 for the device to provide therapyaccording to those parameters or settings 282. As such, the new, secondlevel of parameters or settings is programmed into the subject's therapydevice, and the device then operates according to those new parametersor settings 282 and provides that newly determined course of therapy ortreatment to the subject.

FIG. 18 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. First, a movement disorderdiagnostic device is provided to a subject 370 who has a therapy device,such as a DBS therapy device. The movement disorder diagnostic device isas described herein, but preferably comprises at least one physiologicalor movement sensor for measuring the subject's external body motion, orsome other physiological signal of the subject, where the sensor(s) hasa signal related to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the movement disorder diagnostic device has been provided 370 tothe subject, and the subject has donned or attached the device, the nextstep is to instruct the subject 372 to perform at least one movementdisorder test(s) while the subject is undergoing therapy from thetherapy (e.g., DBS) device, or is under the effects of recentlyadministered therapy therefrom. These instructions may include a list ofwhich test(s) the subject is to perform, directions on how to performthe test, or a combination of both. The instructions to perform a testor tests may be given 372 in person (if in a clinical setting) by aclinician, physician or technician, or more preferably may be providedin an automated or electronic fashion, such as tele- or videoconferencewith a clinician, physician or technician. For example, the instructionto perform the test(s) may be provided in an automated fashion to thesubject via a video display, or a notification or alert message providedvia such a display or perhaps the subject's smart phone, or the like.The instructions are provided 372, either audibly, visually, or acombination thereof. The subject's performance of the tasks is thusaffected by the therapy being provided, or recently provided by thetherapy device.

While the subject is performing the at least one movement disordertest(s) as instructed 372, the step of measuring and quantifying motorsymptoms 374 of the subject based at least in part on the signal of theat least one sensor(s) is performed. The movement disorder diagnosticdevice uses the signal of the at least one sensor(s) to provide anobjective measurement and quantification of the severity of thesubject's motor symptoms while the subject performs the at least onemovement disorder test. The measured and quantified motor symptoms mayinclude specific movement disorder symptoms, side effects frommedication and/or therapy, or combinations thereof. The trained scoringalgorithms of the movement disorder diagnostic device perform variousmeasurements and calculations to provide this objective quantificationof the subject's motor symptoms.

Once the subject's motor symptoms have been measured and quantified 374,data corresponding to these measured and quantified motor symptoms istransmitted to a remote location 376. Typically, the data correspondingto the measured and quantified motor symptoms is an objective score, asdescribed herein, but may be represented in numerous ways and means.Preferably, the data is transmitted 376 directly from the subject'smovement disorder diagnostic device using at least on electricalcomponent for sending or transmitting signals. Preferably, suchtransmission is performed wirelessly as described herein, though it maybe performed by use of a tethered or docking station system where thediagnostic device is placed in contact with the tethered communicationssystem or docking station which then transmits the data. As describedherein, the data is preferably transmitted directly to a remote locationwhere a clinician, physician or technician can access the dataimmediately or at will for analysis and review. Additionally oralternatively, the data may be transmitted to a form of data storagesuch as a centralized server, cloud-based server, or other storagedatabase. The clinician, physician or technician can then either accessthe data directly from a computer device to which the data istransmitted 376 or from the storage system in order to review andanalyze the data. Using this data, the clinician, physician ortechnician then determines at least two optional groups of therapy(e.g., DBS) parameters or settings 373 based on the data and with thegoal of improving the subject's movement in a manner as describedherein. The at least two optional groups of parameters or settingspreferably each correspond to a different mode of therapy or treatmentthat addresses the subject's needs as determined based on the measuredand quantified motor symptom data, as well as other data, goals, orobjectives. In other words, if the system determines that the subject isexperiencing a very strong tremor and gait disturbances, suchdetermination being made as a result of the measurement of the subject'smovement and quantifying the severity of the tremor and gaitdisturbance, one of the at least two optional groups of parameters orsettings 378 would aim to reduce or minimize the tremor and the otherwould aim to reduce or minimize the gait disturbances the subject isexperiencing. As noted, the determination of at least two optionalgroups of parameters or settings may be based on any number ofconstraints or desired results for the subject, not solely the immediatesymptom or side effect the subject is experiencing. For example, if thesubject's main concern is reducing or minimizing symptom occurrence andor severity, the clinician, physician or technician, or algorithm willtake this desired goal into account when determining the at least twooptional groups of parameters or settings. Similarly, the determinationof settings or parameters may be based on a desired reduction orminimization of side effects from medication or the therapy. Also, thedetermination may be made to balance multiple desired results, such asif a slightly higher rate of occurrence of symptoms is acceptable to thesubject in exchange for a minimization of side effects. Other examplesof desired results that may be used to determine the second level oftherapy parameters or settings for all embodiments include, but are notlimited to, a therapeutic window (in terms of time or some other factor)in which the subject most positively responds to therapy, battery life,and other such constraints that might be considered in terms ofoptimizing the therapy parameters or settings. In any determination, thesubject and the clinician, physician or technician decide what theinitial desired result is, and these desired results, goals, orconstraints are programmed into the algorithm for the decision makingprocess. In some embodiments, the desired result, goal or constraintsmay be edited or changed in order to allow the second level ofparameters to provide optimal treatment for the subject.

Once the at least two optional groups of therapy parameters or settingshas been determined or decided upon, at least one of the optional groupsis selected for use 377. Then, the at least one selected optional groupof parameters or settings is then transmitted to the subject's therapydevice 388 (e.g., DBS device). The therapy device preferably comprisesat least one electronic component for receiving such signals, and usesthis at least one component to receive a signal(s) comprising the secondlevel of therapy parameters or settings. The at least one selectedoptional group of parameters or settings are preferably transmitted 388via wireless communication, as described herein, between the remotelocation and the subject's therapy device. Once the therapy devicereceives the transmitted second level of therapy parameters or settings,the selected optional group of parameters or settings is then entered into the subject's therapy device 390 for the device to provide therapyaccording to those parameters or settings 392. As such, the new,selected optional group of parameters or settings is programmed into thesubject's therapy device, and the device then operates according tothose new parameters or settings 392 and provides that newly determinedcourse of therapy or treatment to the subject.

FIG. 19 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. First, a movement disorderdiagnostic device is provided to a subject 470 who has a therapy device,such as a DBS therapy device. The movement disorder diagnostic device isas described herein, but preferably comprises at least one physiologicalor movement sensor for measuring the subject's external body motion, orsome other physiological signal of the subject, where the sensor(s) hasa signal related to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the movement disorder diagnostic device has been provided 470 tothe subject, and the subject has donned or attached the device, the nextstep is to instruct the subject 472 to perform at least one movementdisorder test(s) while the subject is undergoing therapy from thetherapy (e.g., DBS) device, or is under the effects of recentlyadministered therapy therefrom. These instructions may include a list ofwhich test(s) the subject is to perform, directions on how to performthe test, or a combination of both. The instructions to perform a testor tests may be given 472 in person (if in a clinical setting) by aclinician, physician or technician, or more preferably may be providedin an automated or electronic fashion. For example, the instruction toperform the test(s) may be provided in an automated fashion to thesubject via a video display, or a notification or alert message providedvia such a display or perhaps the subject's smart phone, on a displaydevice via tele- or videoconference with a clinician, physician ortechnician, or the like. The instructions are provided 472, eitheraudibly, visually, or a combination thereof. The subject's performanceof the tasks is thus affected by the therapy being provided, or recentlyprovided by the therapy device.

While the subject is performing the at least one movement disordertest(s) as instructed 472, the step of measuring and quantifying motorsymptoms 474 of the subject based at least in part on the signal of theat least one sensor(s) is performed. The movement disorder diagnosticdevice uses the signal of the at least one sensor(s) to provide anobjective measurement and quantification of the severity of thesubject's motor symptoms while the subject performs the at least onemovement disorder test. The measured and quantified motor symptoms mayinclude specific movement disorder symptoms, side effects frommedication and/or therapy, or combinations thereof. The trained scoringalgorithms of the movement disorder diagnostic device perform variousmeasurements and calculations to provide this objective quantificationof the subject's motor symptoms.

Once the subject's motor symptoms have been measured and quantified 474,data corresponding to these measured and quantified motor symptoms istransmitted to a remote location 476. Typically, the data correspondingto the measured and quantified motor symptoms is an objective score, asdescribed herein, but may be represented in numerous ways and means.Preferably, the data is transmitted 476 directly from the subject'smovement disorder diagnostic device using at least on electricalcomponent for sending or transmitting signals. Preferably, suchtransmission is performed wirelessly as described herein, though it maybe performed by use of a tethered or docking station system where thediagnostic device is placed in contact with the tethered communicationssystem or docking station which then transmits the data. As describedherein, the data is preferably transmitted directly to a remote locationwhere a clinician, physician or technician can access the dataimmediately or at will for analysis and review. Additionally oralternatively, the data may be transmitted to a form of data storagesuch as a centralized server, cloud-based server, or other storagedatabase. The clinician, physician or technician can then either accessthe data directly from a computer device to which the data istransmitted 476 or from the storage system in order to review andanalyze the data. Using this data, the clinician, physician ortechnician then determines a second level of therapy (e.g., DBS)parameters or settings 478 based on the data and with the goal ofimproving the subject's movement in a manner as described herein. Thissecond level of parameters or settings preferably corresponds to a modeof therapy or treatment that addresses the subject's needs as determinedbased on the measured and quantified motor symptom data, as well asother data, goals, or objectives. In other words, if the clinician orsystem determines that the subject is experiencing a very strong tremor,such determination being made as a result of the measurement of thesubject's movement and quantifying the severity of the tremor, thesecond level of parameters or settings 478 would aim to reduce orminimize the tremor the subject is experiencing. As noted, thedetermination of a second level of parameters or settings may be basedon any number of constraints or desired results for the subject, notsolely the immediate symptom or side effect the subject is experiencing.For example, if the subject's main concern is reducing or minimizingsymptom occurrence and or severity, the clinician, physician ortechnician, or algorithm will take this desired goal into account whendetermining the second level of parameters or settings. Similarly, thedetermination of settings or parameters may be based on a desiredreduction or minimization of side effects from medication or thetherapy. Also, the determination may be made to balance multiple desiredresults, such as if a slightly higher rate of occurrence of symptoms isacceptable to the subject in exchange for a minimization of sideeffects. Other examples of desired results that may be used to determinethe second level of therapy parameters or settings for all embodimentsinclude, but are not limited to, a therapeutic window (in terms of timeor some other factor) in which the subject most positively responds totherapy, battery life, and other such constraints that might beconsidered in terms of optimizing the therapy parameters or settings. Inany determination, the subject and the clinician, physician ortechnician decide what the initial desired result is, and these desiredresults, goals, or constraints are programmed into the algorithm for thedecision making process. In some embodiments, the desired result, goalor constraints may be edited or changed in order to allow the secondlevel of parameters to provide optimal treatment for the subject.

Once the second level of therapy parameters or settings has beendetermined or decided upon, this second level of parameters or settingsis then transmitted to the subject's therapy device 479 (e.g., DBSdevice). The therapy device preferably comprises at least one electroniccomponent for receiving such signals, and uses this at least onecomponent to receive a signal(s) comprising the second level of therapyparameters or settings. The parameters or settings are preferablytransmitted 479 via wireless communication, as described herein, betweenthe remote location and the subject's therapy device. Preferably, theclinician, physician or technician updates the settings or parameters inthe software package and these parameters or settings are transmittedand automatically entered 481 into the subject's device requiring nodirect interaction between the clinician, physician or technician andthe subject's therapy device. Thus, once the therapy device receives thetransmitted second level of therapy parameters or settings, the secondlevel of parameters or settings is then automatically entered in to thesubject's therapy device 481 for the device to provide therapy accordingto those parameters or settings 482. As such, the new, second level ofparameters or settings is programmed into the subject's therapy device,and the device then operates according to those new parameters orsettings 482 and provides that newly determined course of therapy ortreatment to the subject. Thus, the system measures and quantifies thesubject's symptoms 474, allows a remotely located clinician to determinea second level of therapy parameters or settings that would addressthose symptoms 478, the second level of parameters or settings istransmitted 479 and automatically programmed 481 into the subject'stherapy device 480, and the therapy device implements the second levelof parameters or setting to in fact address the subject's symptoms 482.

FIG. 20 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. First, a movement disorderdiagnostic device is provided to a subject 570 who has a therapy device,such as a DBS therapy device. The movement disorder diagnostic device isas described herein, but preferably comprises at least one physiologicalor movement sensor for measuring the subject's external body motion, orsome other physiological signal of the subject, where the sensor(s) hasa signal related to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the movement disorder diagnostic device has been provided 570 tothe subject, and the subject has donned or attached the device, the nextstep is to instruct the subject 572 to perform at least one movementdisorder test(s) while the subject is undergoing therapy from thetherapy (e.g., DBS) device, or is under the effects of recentlyadministered therapy therefrom. These instructions may include a list ofwhich test(s) the subject is to perform, directions on how to performthe test, or a combination of both. The instructions to perform a testor tests may be given 572 in person (if in a clinical setting) by aclinician, physician or technician, or more preferably may be providedin an automated or electronic fashion. For example, the instruction toperform the test(s) may be provided in an automated fashion to thesubject via a video display, or a notification or alert message providedvia such a display or perhaps the subject's smart phone, on a displaydevice via tele- or videoconference with a clinician, physician ortechnician, or the like. The instructions are provided 572, eitheraudibly, visually, or a combination thereof. The subject's performanceof the tasks is thus affected by the therapy being provided, or recentlyprovided by the therapy device.

While the subject is performing the at least one movement disordertest(s) as instructed 572, the step of measuring and quantifying motorsymptoms 574 of the subject based at least in part on the signal of theat least one sensor(s) is performed. The movement disorder diagnosticdevice uses the signal of the at least one sensor(s) to provide anobjective measurement and quantification of the severity of thesubject's motor symptoms while the subject performs the at least onemovement disorder test. The measured and quantified motor symptoms mayinclude specific movement disorder symptoms, side effects frommedication and/or therapy, or combinations thereof. The trained scoringalgorithms of the movement disorder diagnostic device perform variousmeasurements and calculations to provide this objective quantificationof the subject's motor symptoms.

Once the subject's motor symptoms have been measured and quantified 574,data corresponding to these measured and quantified motor symptoms istransmitted to a remote location 576. Typically, the data correspondingto the measured and quantified motor symptoms is an objective score, asdescribed herein, but may be represented in numerous ways and means.Preferably, the data is transmitted 576 directly from the subject'smovement disorder diagnostic device using at least on electricalcomponent for sending or transmitting signals. Preferably, suchtransmission is performed wirelessly as described herein, though it maybe performed by use of a tethered or docking station system where thediagnostic device is placed in contact with the tethered communicationssystem or docking station which then transmits the data. As describedherein, the data is preferably transmitted directly to a remote locationwhere a clinician, physician or technician can access the dataimmediately or at will for analysis and review. Additionally oralternatively, the data may be transmitted to a form of data storagesuch as a centralized server, cloud-based server, or other storagedatabase. The clinician, physician or technician can then either accessthe data directly from a computer device to which the data istransmitted 576 or from the storage system in order to review andanalyze the data. Using this data, the clinician, physician ortechnician then determines a second level of therapy (e.g., DBS)parameters or settings 578 based on the data and with the goal ofimproving the subject's movement in a manner as described herein. Thissecond level of parameters or settings preferably corresponds to a modeof therapy or treatment that addresses the subject's needs as determinedbased on the measured and quantified motor symptom data, as well asother data, goals, or objectives. In other words, if the clinician orsystem determines that the subject is experiencing a very strong tremor,such determination being made as a result of the measurement of thesubject's movement and quantifying the severity of the tremor, thesecond level of parameters or settings 578 would aim to reduce orminimize the tremor the subject is experiencing. As noted, thedetermination of a second level of parameters or settings may be basedon any number of constraints or desired results for the subject, notsolely the immediate symptom or side effect the subject is experiencing.For example, if the subject's main concern is reducing or minimizingsymptom occurrence and or severity, the clinician, physician ortechnician, or algorithm will take this desired goal into account whendetermining the second level of parameters or settings. Similarly, thedetermination of settings or parameters may be based on a desiredreduction or minimization of side effects from medication or thetherapy. Also, the determination may be made to balance multiple desiredresults, such as if a slightly higher rate of occurrence of symptoms isacceptable to the subject in exchange for a minimization of sideeffects. Other examples of desired results that may be used to determinethe second level of therapy parameters or settings for all embodimentsinclude, but are not limited to, a therapeutic window (in terms of timeor some other factor) in which the subject most positively responds totherapy, battery life, and other such constraints that might beconsidered in terms of optimizing the therapy parameters or settings. Inany determination, the subject and the clinician, physician ortechnician decide what the initial desired result is, and these desiredresults, goals, or constraints are programmed into the algorithm for thedecision making process. In some embodiments, the desired result, goalor constraints may be edited or changed in order to allow the secondlevel of parameters to provide optimal treatment for the subject.

Once the second level of therapy parameters or settings has beendetermined or decided upon, this second level of parameters or settingsis then transmitted to the subject's therapy device 579 (e.g., DBSdevice). The therapy device preferably comprises at least one electroniccomponent for receiving such signals, and uses this at least onecomponent to receive a signal(s) comprising the second level of therapyparameters or settings. The parameters or settings are preferablytransmitted 579 via wireless communication, as described herein, betweenthe remote location and the subject's therapy device. Once the therapydevice receives the transmitted second level of therapy parameters orsettings, the second level of parameters or settings is then entered into the subject's therapy device 580 for the device to provide therapyaccording to those parameters or settings 582. As such, the new, secondlevel of parameters or settings is programmed into the subject's therapydevice, and the device then operates according to those new parametersor settings 582 and provides that newly determined course of therapy ortreatment to the subject. In this particular embodiment, the systemadditionally uploads or transmits 594 the second level of DBS parametersor setting and/or the quantified motor symptom data to a remote locationsuch as a database or server for storage and or access by the clinicianat a later time. The uploading or transmission of the parameters orsettings and/or data is preferably done substantially simultaneouslywith transmitting the parameters or settings to the subject's therapydevice, however it can be done at a later time. Thus, the systemmeasures and quantifies the subject's symptoms 574, allows a remotelylocated clinician to determine a second level of therapy parameters orsettings that would address those symptoms 578, the second level ofparameters or settings is transmitted 579 and programmed into thesubject's therapy device 580, and the therapy device implements thesecond level of parameters or setting to in fact address the subject'ssymptoms 582, and additionally the parameters or settings and/or thequantified movement data is transmitted to a database or other storagemedium 594 for later access and/or storage of the data.

FIG. 21 depicts a normal human brain labeled with various lobes andcortexes known in the art. Of particular note within the scope of thepresent invention is the motor cortex. The primary motor cortex, or M1,is one of the principal brain areas involved in motor function. M1 islocated in the frontal lobe of the brain, along a bump called theprecentral gyms. The role of the primary motor cortex is to generateneural impulses that control the execution of movement. Signals from M1cross the body's midline to activate skeletal muscles on the oppositeside of the body, meaning that the left hemisphere of the brain controlsthe right side of the body, and the right hemisphere controls the leftside of the body. Every part of the body is represented in the primarymotor cortex, and these representations are arranged somatotopically—thefoot is next to the leg which is next to the trunk which is next to thearm and the hand. The amount of brain matter devoted to any particularbody part represents the amount of control that the primary motor cortexhas over that body part. For example, a lot of cortical space isrequired to control the complex movements of the hand and fingers, andthese body parts have larger representations in M1 than the trunk orlegs, whose muscle patterns are relatively simple. This disproportionatemap of the body in the motor cortex is called the motor homunculus.Other regions of the cortex involved in motor function are called thesecondary motor cortices. These regions include the posterior parietalcortex, the premotor cortex, and the supplementary motor area (SMA). Theposterior parietal cortex is involved in transforming visual informationinto motor commands. For example, the posterior parietal cortex would beinvolved in determining how to steer the arm to a glass of water basedon where the glass is located in space. The posterior parietal areassend this information on to the premotor cortex and the supplementarymotor area. The premotor cortex lies just in front of (anterior to) theprimary motor cortex. It is involved in the sensory guidance ofmovement, and controls the more proximal muscles and trunk muscles ofthe body. In our example, the premotor cortex would help to orient thebody before reaching for the glass of water. The supplementary motorarea lies above, or medial to, the premotor area, also in front of theprimary motor cortex. It is involved in the planning of complexmovements and in coordinating two-handed movements. The supplementarymotor area and the premotor regions both send information to the primarymotor cortex as well as to brainstem motor regions. Neurons in M1, SMAand premotor cortex give rise to the fibers of the corticospinal tract.The corticospinal tract is the only direct pathway from the cortex tothe spine and is composed of over a million fibers. These fibers descendthrough the brainstem where the majority of them cross over to theopposite side of the body. After crossing, the fibers continue todescend through the spine, terminating at the appropriate spinal levels.The corticospinal tract is the main pathway for control of voluntarymovement in humans. There are other motor pathways which originate fromsubcortical groups of motor neurons (nuclei). These pathways controlposture and balance, coarse movements of the proximal muscles, andcoordinate head, neck and eye movements in response to visual targets.Subcortical pathways can modify voluntary movement through interneuronalcircuits in the spine and through projections to cortical motor regions.

FIG. 22 is an image depicting the motor cortex of a human brain withcorresponding parts of the body that are controlled by the regions ofthe motor cortex. The size of the body part in the image is directlyrelated to the amount of the motor cortex that is dedicated to controlof that body part. For example the various portions of a person's handand face are much larger than any portion of the leg. Thus, much more ofthe motor cortex is directed to control of the hands and face than theleg. Knowledge of these relationships, and mapping of the specificregions of the brain for particular patient which control the bodymovement, allows the present invention to provide highly-specific,targeted and tuned therapy to the subject to alleviate his or hersymptoms.

FIG. 23 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. This particular embodiment isenvisioned to be performed in an automated fashion, by an algorithm(s),with little or no interaction required with a clinician, physician ortechnician, and where the subject is located remotely from a clinician,physician or technician, such as at home. First, a subject who has atherapy device, such as a DBS therapy device, wears a movement disorderdiagnostic device 90. The DBS device further comprises at least onedual-mode lead comprising a plurality of contacts, each contact adaptedto both provide stimulation to the subject's brain as well as to senseor acquire signals from the subject's brain, particularly to measurebrain activity. The therapy device preferably has a first level oftherapy parameters or settings already programmed or entered into thedevice. The movement disorder diagnostic device is as described herein,but preferably comprises at least one physiological or movement sensorfor measuring the subject's external body motion, or some otherphysiological signal of the subject, where the sensor(s) has a signalrelated to the subject's motion or other physiological signal.Preferably, the movement disorder diagnostic device is a single unit,though may be multiple units (e.g., separate sensor unit andcommand/transceiver module), and is adapted to be worn or attached to aportion of the subject's body such that the sensor(s) of the movementdisorder diagnostic device are able to measure the movement of thatparticular portion of the subject's body.

Once the subject is wearing the movement disorder diagnostic device 600,the diagnostic device then identifies or determines what, if any,activity, movement or motion the subject is performing and brainactivity is measured and acquired 602. This identification ordetermination is made based on the signal from the at least onephysiological or movement sensor of the diagnostic device, and the brainactivity is measured with a dual-mode DBS lead adapted to providestimulation as well as measure signals from the subject. Theidentification or determination may be made by the subject who maymanually input the new activity, movement or motion into the device, bya clinician either local or remote to the subject, who may interpret thesignals from the at least one sensor and identify or determine theactivity, movement or motion, or more preferably, automatically by thedevice. Automatic identification or determination of the subject'sactivity, movement, or motion is preferably performed by a processorcontained within the device which may include a separate algorithm foractivity identification or determination, or the measurement andquantification algorithms may be able to perform this function.Preferably, even where the subject or a clinician, physician ortechnician identifies or determines and inputs the activity, movement ormotion, the device uses the signal from the at least one sensor toestimate or predict the activity, movement or motion, and allows theparticular user to confirm the identified or determined activity,movement or motion or to override the suggested identification and inputanother. The system may provide the user with several options to selectfrom as well, all based on the signals from the at least one sensor.

Once the subject's activity, movement or motion has been identified ordetermined and brain activity measured 602, the next step is to identifyor determine any motor symptoms of a movement disorder or side effectsof a treatment 604 that the subject is experiencing as experienced whileperforming the identified or determined movement, motion or activity.The identification or determination of symptoms or side effects 604 issimilarly capable of being performed by either a human user orautomatically, or combination thereof. Much like the activityidentification 602 above, the subject or a clinician may input into thesystem any known symptoms or side effects. Preferably though, the systemautomatically identifies or determines the symptoms or side effectsbased at least in part on the signal from the at least one movementsensor and/or the measured brain activity from the dual-mode DBS lead,and at least in part on the identified or determined activity, movementor motion. Again, a separate symptom and side effect identificationalgorithm may utilize the signal from the sensor and the identifiedactivity to identify or determine what symptoms and/or side effects thesubject is experiencing or has experienced. This algorithm may thenpresent options to the subject or to a clinician, again either local orremote, for confirmation or to be rejected.

Next, the step of correlating identified activities, movements ormotions and/or symptoms with measured brain activity 605 is performedusing a processor and correlation algorithm. The external sensors formovement/motion and/or physiological data, and inputted data arecorrelated with measured brain activity in order to identify theportions of the brain that are responsible for causing certain motionsand symptoms. This correlation data is preferably built up over time andstored in local and/or database memory to create a map of correlateddata such that the system can identify movement and/or symptoms based onmeasured brain activity without external measured movement data and/oruser input.

Next, the step of measuring and quantifying the identified or determinedmotor symptoms or side effects 606 of the subject based at least in parton the signal of the at least one movement sensor(s) and/or brainactivity sensor(s). The movement disorder diagnostic device uses thesignal of the at least one movement sensor(s) and/or brain activitysensor(s) to provide an objective measurement and quantification of theseverity of the subject's motor symptoms or side effects while thesubject performs the identified or determined activity, movement ormotion. The measured and quantified motor symptoms or side effects mayinclude specific movement disorder symptoms, side effects frommedication and/or therapy, or combinations thereof. The trained scoringalgorithms of the movement disorder diagnostic device perform variousmeasurements and calculations to provide this objective quantificationof the subject's motor symptoms.

Once the subject's motor symptoms or side effects have been measured andquantified 606, data corresponding to these measured and quantifiedmotor symptoms is entered into a processor comprising an algorithm(s)608 for automated analysis. Typically, the data corresponding to themeasured and quantified motor symptoms is an objective score, asdescribed herein, but may be represented in numerous ways and means.Preferably, the quantified motor symptom data is entered 608 directlyand automatically into the processor and into the determinationalgorithm(s) without the need for any manual human intervention, such askeying in the data.

The processor and its algorithm(s) then analyze the measured andquantified motor symptom data and calculate a second level of therapyparameters or settings 610. This second level of parameters or settingspreferably corresponds to a mode of therapy or treatment that addressesthe subject's needs as determined based on the identified or determinedactivity and symptoms or side effects, and the measured and quantifiedmotor symptom data and brain activity data, as well as other data,goals, or objectives. In other words, if the system determines that, forexample, the subject is experiencing a very strong tremor while driving,such determination being made as a result of the identification of thesubject's activity and symptoms as well as measurement of the subject'smovement and brain activity and quantifying the severity of the tremor,the processor and algorithm would provide a second level of parametersor settings 610 that would reduce or minimize the tremor the subject isexperiencing. As noted, the calculation of a second level of parametersor settings may be based on any number of constraints or desired resultsfor the subject, not solely the immediate symptom or side effect thesubject is experiencing. For example, if the subject's main concern isreducing or minimizing symptom occurrence and or severity, the processorand its algorithms will take this desired goal into account whencalculating the second level of parameters or settings. Similarly, thecalculation of settings or parameters may be based on a desiredreduction or minimization of side effects from medication or thetherapy. Also, the calculation may be made to balance multiple desiredresults, such as if a slightly higher rate of occurrence of symptoms isacceptable to the subject in exchange for a minimization of sideeffects. Other examples of desired results that may be used to determinethe second level of therapy parameters or settings for all embodimentsinclude, but are not limited to, a therapeutic window (in terms of timeor some other factor) in which the subject most positively responds totherapy, battery life, and other such constraints that might beconsidered in terms of optimizing the therapy parameters or settings. Inany determination, the subject and the clinician, physician ortechnician decide what the initial desired result is, and these desiredresults, goals, or constraints are programmed into the processor and itsalgorithm(s) for the decision making process. In some embodiments, thedesired result, goal or constraints may be edited, either by aclinician, physician or technician, or by the subject, in order to allowthe algorithm to most accurately analyze the data in light of theoptimal treatment for the subject.

Once this second level of parameters or settings has been calculated bythe processor and its algorithm(s) 610, the parameters or settings arethen transmitted to the subject's therapy device 612 (e.g., DBS device).The therapy device preferably comprises at least one electroniccomponent for receiving such signals, and uses this at least onecomponent to receive a signal(s) comprising the second level of therapyparameters or settings from the diagnostic device. The parameters orsettings may additionally be transmitted via wireless communication, asdescribed herein, between the subject's therapy device and a remotelocation such as to a database or server for storage, or directly to aremote clinician physician or technician for optional review. Once thetherapy device receives the transmitted 612 second level of therapyparameters or settings, the second level of parameters or settings isthen entered in to the subject's therapy device 614 for the device toprovide therapy according to those parameters or settings. As such, thenew, second level of parameters or settings is programmed into thesubject's therapy device, and the device then operates according tothose new parameters or settings 614 and provides that newly determinedcourse of therapy or treatment to the subject.

FIG. 24 depicts a flow chart representing a method embodiment of thepresent invention for tuning the movement disorder diagnostic devicewith new therapy parameters or settings. This particular embodiment isenvisioned to be performed in an automated fashion, by an algorithm(s),with little or no interaction required with a clinician, physician ortechnician, and where the subject is located remotely from a clinician,physician or technician, such as at home. First, a subject is providedwith a therapy device 650, such as a DBS therapy device. The DBS devicefurther comprises at least one dual-mode lead comprising a plurality ofcontacts, each contact adapted to both provide stimulation to thesubject's brain as well as to sense or acquire signals from thesubject's brain, particularly to measure brain activity. The therapydevice preferably has a first level of therapy parameters or settingsalready programmed or entered into the device.

Once the subject has the therapy device 650, typically implanted, thesystem then identifies or determines what, if any, activity, movement ormotion the subject is performing and brain activity is measured andacquired 652. This identification or determination may be made based onthe measured brain activity, and the brain activity is measured with adual-mode DBS lead adapted to provide stimulation as well as measuresignals from the subject. The identification or determination may bemade by the subject who may manually input the new activity, movement ormotion into the device, by a clinician either local or remote to thesubject, who may interpret the signals from the at least one sensor andidentify or determine the activity, movement or motion, or morepreferably, automatically by the device. Automatic identification ordetermination of the subject's activity, movement, or motion ispreferably performed by a processor contained within the device whichmay include a separate algorithm for activity identification ordetermination, or the measurement and quantification algorithms may beable to perform this function. Preferably, even where the subject or aclinician, physician or technician identifies or determines and inputsthe activity, movement or motion, the device uses the signal from the atleast one sensor to estimate or predict the activity, movement ormotion, and allows the particular user to confirm the identified ordetermined activity, movement or motion or to override the suggestedidentification and input another. The system may provide the user withseveral options to select from as well, all based on the signals fromthe at least one sensor.

Once the subject's activity, movement or motion has been identified ordetermined and brain activity measured 652, the next step is to identifyor determine any motor symptoms of a movement disorder or side effectsof a treatment 654 that the subject is experiencing or has experiencedwhile performing the identified or determined movement, motion oractivity. The identification or determination of symptoms or sideeffects 654 is similarly capable of being performed by either a humanuser or automatically, or combination thereof. Much like the activityidentification 652 above, the subject or a clinician may input into thesystem any known symptoms or side effects. Preferably though, the systemautomatically identifies or determines the symptoms or side effectsbased at least in part on the signal from the at least one movementsensor and/or the measured brain activity from the dual-mode DBS lead,and at least in part on the identified or determined activity, movementor motion. Again, a separate symptom and side effect identificationalgorithm may utilize the signal from the sensor and the identifiedactivity to identify or determine what symptoms and/or side effects thesubject is experiencing or has experienced. This algorithm may thenpresent options to the subject or to a clinician, again either local orremote, for confirmation or to be rejected.

Next, the step of correlating identified activities, movements ormotions and/or symptoms with measured brain activity 655 is performedusing a processor and correlation algorithm. The external sensors formovement/motion and/or physiological data and inputted data arecorrelated with measured brain activity in order to identify theportions of the brain that are responsible for causing certain motionsand symptoms. This correlation data is preferably built up over time andstored in local and/or database memory to create a map of correlateddata such that the system can identify movement and/or symptoms based onmeasured brain activity without external measured movement data and/oruser input.

Next, the step of measuring and quantifying the identified or determinedmotor symptoms or side effects 656 of the subject based at least in parton the signal of the at least one brain activity sensor(s). The movementdisorder diagnostic device uses the signal of the at least one brainactivity sensor(s) to provide an objective measurement andquantification of the severity of the subject's motor symptoms or sideeffects while the subject performs the identified or determinedactivity, movement or motion. The measured and quantified motor symptomsor side effects may include specific movement disorder symptoms, sideeffects from medication and/or therapy, or combinations thereof. Thetrained scoring algorithms of the movement disorder diagnostic deviceperform various measurements and calculations to provide this objectivequantification of the subject's motor symptoms.

Once the subject's motor symptoms or side effects have been measured andquantified 656, data corresponding to these measured and quantifiedmotor symptoms is entered into a processor comprising an algorithm(s)658 for automated analysis. Typically, the data corresponding to themeasured and quantified motor symptoms is an objective score, asdescribed herein, but may be represented in numerous ways and means.Preferably, the quantified motor symptom data is entered 658 directlyand automatically into the processor and into the determinationalgorithm(s) without the need for any manual human intervention, such askeying in the data.

The processor and its algorithm(s) then analyze the measured andquantified motor symptom data and calculate a second level of therapyparameters or settings 660. This second level of parameters or settingspreferably corresponds to a mode of therapy or treatment that addressesthe subject's needs as determined based on the identified or determinedactivity and symptoms or side effects, and the measured and quantifiedmotor symptom data and brain activity data, as well as other data,goals, or objectives. In other words, if the system determines that, forexample, the subject is experiencing a very strong tremor while driving,such determination being made as a result of the identification of thesubject's activity and symptoms as well as measurement of the subject'smovement and brain activity and quantifying the severity of the tremor,the processor and algorithm would provide a second level of parametersor settings 610 that would reduce or minimize the tremor the subject isexperiencing. As noted, the calculation of a second level of parametersor settings may be based on any number of constraints or desired resultsfor the subject, not solely the immediate symptom or side effect thesubject is experiencing. For example, if the subject's main concern isreducing or minimizing symptom occurrence and or severity, the processorand its algorithms will take this desired goal into account whencalculating the second level of parameters or settings. Similarly, thecalculation of settings or parameters may be based on a desiredreduction or minimization of side effects from medication or thetherapy. Also, the calculation may be made to balance multiple desiredresults, such as if a slightly higher rate of occurrence of symptoms isacceptable to the subject in exchange for a minimization of sideeffects. Other examples of desired results that may be used to determinethe second level of therapy parameters or settings for all embodimentsinclude, but are not limited to, a therapeutic window (in terms of timeor some other factor) in which the subject most positively responds totherapy, battery life, and other such constraints that might beconsidered in terms of optimizing the therapy parameters or settings. Inany determination, the subject and the clinician, physician ortechnician decide what the initial desired result is, and these desiredresults, goals, or constraints are programmed into the processor and itsalgorithm(s) for the decision making process. In some embodiments, thedesired result, goal or constraints may be edited, either by aclinician, physician or technician, or by the subject, in order to allowthe algorithm to most accurately analyze the data in light of theoptimal treatment for the subject.

Once this second level of parameters or settings has been calculated bythe processor and its algorithm(s) 660, the parameters or settings arethen transmitted to the subject's therapy device 612 (e.g., DBS device).The therapy device preferably comprises at least one electroniccomponent for receiving such signals, and uses this at least onecomponent to receive a signal(s) comprising the second level of therapyparameters or settings from the diagnostic device. The parameters orsettings may additionally transmitted via wireless communication, asdescribed herein, between the subject's therapy device and a remotelocation such as to a database or server for storage, or directly to aremote clinician physician or technician for optional review. Once thetherapy device receives the transmitted 662 second level of therapyparameters or settings, the second level of parameters or settings isthen entered in to the subject's therapy device 664 for the device toprovide therapy according to those parameters or settings. As such, thenew, second level of parameters or settings is programmed into thesubject's therapy device, and the device then operates according tothose new parameters or settings 664 and provides that newly determinedcourse of therapy or treatment to the subject.

FIG. 25 is a flow chart depicting an embodiment of the testing andmeasurement process for obtaining data related to a subject's externalbody movement or motion and/or physiological data and correlating suchwith measured brain activity to map the areas of the subject's brainrelated to particular types of motion. As an initial point, a subjectfor purposes of the present embodiment must have a therapy device,typically an implanted DBS device, already surgically implanted or beingimplanted. Once the DBS device is disposed within the subject, adiagnostic device is provided for the subject to wear 700. Preferablythe diagnostic device comprises at least one sensor for measuringexternal body motion and/or at least one sensor for measuring otherphysiological signals of the subject, for example, electrophysiologicalsignals such as EMG, EEG, EOG, and the like. The DBS device alsopreferably has a first level of therapy parameters already programmedinto it for operation to deliver therapeutic electrical stimulation tothe subject according to the programmed first level of parameters. Thisfirst level of parameters may be clinically decided upon and set by aclinician, or it may be a semi-automatically or automatically providedset of parameters provided by algorithms for calculating suggestedparameters, as described herein. The therapeutic electrical stimulationis provided to the subject via dual-mode DBS leads, each preferably witha plurality of contacts. Also preferably, each of these contacts iscapable of both providing electrical field stimulation to the subject,but is also adapted to acquire signals from the subject's body, such aselectrical or physiological signals. The fact that the contacts, or atleast some thereof, are capable of both providing electrical therapy andreceiving electrical signals is the basis of the dual-modedesignation—they operate in both transmission and reception modes withrespect to electrical signals. Once the subject has both a DBS or othertherapy device and is wearing the diagnostic device, the subjectperforms 702 either a directed or instructed movement disorder test, orgoes about performing activities of daily living. While the subject ismoving, the diagnostic device measures the subject's external motion704, using external body motion sensors, and/or other physiologicalsignals, using physiological sensors, from the subject, andsubstantially simultaneously 708 measures the subject's brain activity706 using the therapy device's (e.g., DBS device) implanted dual-modeleads with a plurality of contacts each adapted to both transmit signals(electrical impulses for therapeutic excitation of the brain) and toacquire signals (electrical signals from the brain indicating brainactivity). The data is preferably obtained substantially simultaneouslyin order to capture the exact movement and exact brain activity thatcoincide with each other. Time lapses in the measurement may not bereconcilable given the temporal nature of the movement and brainactivity, so substantially simultaneous measurement allows the system tomore accurately carry out the step of correlating 710 the external bodymotion and/or physiological data with the measured brain activity.Continuous or repeated measurements allow for the correlations betweenspecific movements (including normal and/or symptomatic movement) andexcitation or activity of specific portions of the subject's brain to bemapped 712 to each other such that the system effectively learns whichportions of the brain and can identify the portions or combination ofbrain structures (possibly down to the single-neuronal level) of thebrain that is/are responsible for a given normal or symptomaticmovement. Such brain mapping allows the system to provide finely tuned,highly specific and tailored electrical stimulation from the DBS unitand leads to excite or suppress activity of the specific brain portionor structure relevant to a symptoms symptomatic movement.

FIGS. 26A-B are images depicting results from a brain-mapping sessionrelated to the subject's external body motion. FIG. 26A depicts detectedarm movement brain activity 750 that corresponds to areas of the brainthat were activated during the commission or performance of various armmovements. Similarly, FIG. 26B depicts detected leg movement brainactivity 760 during performance of leg movements. Typical brain mappingperformed by measuring electrical brain activity from exteriorelectrodes or interior electrodes implanted either just on or inside theskull, or on the surface of the brain. The present invention insteadutilizes the contacts location each DBS lead to not only transmitelectrical stimulation therapy, but also to acquire signals from withinthe subject's brain, more accurately mapping the location of activatedneurons. ‘During a mapping session, either clinical with prescribedmovements or during normal activities of daily living, the dual-mode DBSleads acquired signals from the subject's brain indicating the brainwave activity at a given moment. That acquired brain wave activity isthen correlated to the known or measured physical, external bodymovements and identified as, in the present case, arm brain waveactivity 750 or leg brain wave activity 760. Thus, the system canidentify the areas, regions, or pathways through multiple areas orregions of the subject's brain that are responsible at least partially,for particular movements, thus allowing for more targeted therapyparameters that address the subject's specific needs as well as workingwith other desired constraints for the operation of the therapy device.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the present inventionwithout departing from the spirit and scope of the invention. Thus, itis intended that the present invention cover the modifications andvariations of this invention provided they come within the scope of theappended claims and their equivalents.

What is claimed:
 1. A treatment or therapy system adapted to reduceseverity and/or occurrence of a subject's movement disorder symptomsand/or side effects of treatment or therapy of the subject's movementdisorder provided by a treatment or therapy device comprising: a brainactivity measurement component adapted to measure a subject's brainactivity during at least a first and second time periods; a movementdisorder diagnostic device comprising at least one movement sensoradapted to measure the subject's movement disorder symptoms and/or sideeffects of treatment or therapy of the subject's movement disorderduring each of the at least first and second time periods; at least oneprocessor comprising at least one quantification algorithm adapted tocalculate a quantification of severity of the subject's movementdisorder symptoms and/or side effects of treatment or therapy of thesubject's movement disorder during each of the at least first and secondtime periods substantially simultaneously with the measurement of thesubject's movement disorder symptoms and/or side effects of treatment ortherapy; a treatment or therapy device comprising at least one interfaceadapted to automatically change or to enable manual changing ofparameters of the subject's treatment or therapy based at least in parton the at least first and/or second time period quantifications of theseverity of the symptoms and/or side effects; a correlation algorithmcomprised in the at least one processor or an additional processor andadapted to determine the brain activity that minimizes the measuredsymptoms and/or side effects by correlating the measured symptoms and/orside effects and the first and second quantifications of severity withthe simultaneously measured brain activity to map the part(s) of thesubject's brain responsible for the symptoms and/or side effects; atuning algorithm comprised in the at least one processor or theadditional processor and trained based on the determined brain activitythat minimizes the measured symptoms and/or side effects, the tuningalgorithm further adapted to calculate a suggested set of treatment ortherapy parameters based at least in part on the measured brainactivity, the calculated quantifications of severity, and measuredsymptoms and/or side effects, the suggested set of parameters adapted tobe reviewed and approved by a clinician, physician, or technician; andthe at least one interface of the treatment or therapy device is furtheradapted to automatically enter or to enable manual entering of approvedtreatment or therapy parameters into the treatment or therapy devicesuch that the treatment or therapy device provides treatment or therapyto the subject based on the approved parameters.
 2. The system of claim1, wherein the correlation algorithm is a machine learning algorithm. 3.The system of claim 2, further comprising at least one interface adaptedto receive subject input corresponding to personal demographicinformation of the subject and/or to the subject's subjectiveobservations and/or assessments of the occurrence and/or severity ofmovement disorder symptoms and/or side effects of treatment or therapyof the subject's movement disorder during the at least first timeperiod, and the quantification algorithm is adapted to further performits calculation, the correlation algorithm is adapted to further performits correlation, and/or the tuning algorithm is further adapted toperform its calculation based at least further in part on the subjectinput.
 4. The system of claim 2, wherein the brain activity measurementcomponent comprises at least one dual-mode deep brain stimulation (DBS)lead with at least one contact capable of providing electricalstimulation and acquiring physiological signals.
 5. The system of claim1, further comprising a display device adapted to receive the measuredbrain activity as input and to display such measured brain activity inthe form of a 2D or 3D image of the subject's brain concurrently with atuning map presenting the calculated quantification of severity ofsymptoms and/or side effects associated with the measured brain activitybeing displayed.
 6. The system of claim 3, wherein the brain activitymeasurement component is further adapted to measure the subject's brainactivity during at least a third time period, and the tuning algorithmis further adapted to calculate the suggested set of therapy ortreatment parameters based at least in part on the brain activitymeasured during the third time period, but not on the measured symptomsand/or side effects.
 7. The system of claim 4, wherein the at least onedual-mode DBS lead is adapted to simultaneously provide electricalstimulation from one or more of the plurality of contacts on the leadand acquire electrophysiological signals from the subject from one ormore of the plurality of contacts on the lead.
 8. A treatment or therapysystem adapted to reduce severity and/or occurrence of a subject'smovement disorder symptoms and/or side effects of treatment or therapyof the subject's movement disorder provided by a treatment or therapydevice comprising: a brain activity measurement component adapted tomeasure a subject's brain activity during at least a first and secondtime periods; a movement disorder diagnostic device comprising at leastone movement sensor adapted to measure the subject's movement disordersymptoms and/or side effects of treatment or therapy of the subject'smovement disorder during each of the at least first and second timeperiods; at least one processor comprising at least one quantificationalgorithm adapted to calculate a quantification of severity of thesubject's movement disorder symptoms and/or side effects of treatment ortherapy of the subject's movement disorder during each of the at leastfirst and second time periods substantially simultaneously with themeasurement of the subject's movement disorder symptoms and/or sideeffects of treatment or therapy; a treatment or therapy devicecomprising at least one interface adapted to automatically change orenable manual changing of parameters of the subject's treatment ortherapy based at least in part on the at least first and/or second timeperiod quantifications of the severity of the symptoms and/or sideeffects; a correlation algorithm comprised in the at least one processoror an additional processor and adapted to determine the brain activitythat minimizes the measured symptoms and/or side effects by correlatingthe measured symptoms and/or side effects and the first and secondquantifications of severity with the simultaneously measured brainactivity to map the part(s) of the subject's brain responsible for thesymptoms and/or side effects; tuning algorithm comprised in the at leastone processor or the additional processor and trained based on thedetermined brain activity that minimizes the measured symptoms and/orside effects, the tuning algorithm further adapted to calculate asuggested set of treatment or therapy parameters based at least in parton the measured brain activity, the calculated quantifications ofseverity, and measured symptoms and/or side effects; and the at leastone interface of the treatment or therapy device is further adapted toautomatically enter or to enable manual entering of the suggested set oftreatment or therapy parameters into the treatment or therapy devicesuch that the treatment or therapy device provides treatment or therapyto the subject based on the suggested set of parameters.
 9. The systemof claim 8, wherein the correlation algorithm is a machine learningalgorithm.
 10. The system of claim 9, further comprising at least oneinterface adapted to receive subject input corresponding to personaldemographic information of the subject and/or to the subject'ssubjective observations and/or assessments of the occurrence and/orseverity of movement disorder symptoms and/or side effects of treatmentor therapy of the subject's movement disorder during the at least firsttime period, and the quantification algorithm is adapted to furtherperform its calculation, the correlation algorithm is adapted to furtherperform its correlation, and/or the tuning algorithm is further adaptedto perform its calculation based at least further in part on the subjectinput.
 11. The system of claim 9, wherein the brain activity measurementcomponent comprises at least one dual-mode deep brain stimulation (DBS)lead with a plurality of contacts adapted to provide electricalstimulation and to acquire physiological signals.
 12. The system ofclaim 8, further comprising a display device adapted to receive themeasured brain activity as input and to display such measured brainactivity in the form of a 2D or 3D image of the subject's brainconcurrently with a tuning map presenting the calculated quantificationof severity of symptoms and/or side effects associated with the measuredbrain activity being displayed.
 13. The system of claim 8, furthercomprising the step of, after training the tuning algorithm, measuringthe subject's brain activity during a third time period, and thecalculated suggested set of therapy or treatment parameters is based atleast in part on the brain activity measured during the third timeperiod, but not on the measured symptoms and/or side effects.
 14. Thesystem of claim 11, wherein the at least one dual-mode DBS lead isadapted to simultaneously provide electrical stimulation from one ormore of the plurality of contacts on the lead and acquireelectrophysiological signals from the subject from one or more of theplurality of contacts on the lead.
 15. A treatment or therapy systemadapted to reduce severity and/or occurrence of a subject's movementdisorder symptoms and/or side effects of treatment or therapy of thesubject's movement disorder provided by a treatment or therapy devicecomprising: a brain activity measurement component adapted to measure asubject's brain activity during at least a first time period; at leastone processing component comprising at least one interface adapted toreceive subject input corresponding to personal demographic informationof the subject and to the subject's subjective observations andassessments of the occurrence and/or severity of movement disordersymptoms and side effects of treatment or therapy of the subject'smovement disorder during the at least first time period; a correlationalgorithm comprised in the at least one processing component or anadditional processing component and adapted to determine the brainactivity that minimizes the subjectively observed and/or assessed,symptoms and/or side effects by correlating the subject input with themeasured brain activity, each during the at least first time period, tomap the part(s) of the subject's brain responsible for the symptomsand/or side effects; a tuning algorithm comprised in the at least oneprocessor or the additional processor and trained based on thedetermined brain activity that minimizes the measured symptoms and/orside effects, the tuning algorithm further adapted to calculate asuggested set of treatment or therapy parameters based at least in parton the determined brain activity that minimizes the symptoms and/or sideeffects; and the at least one interface of the treatment or therapydevice is further adapted to automatically enter or to enable manualentering of the suggested set of treatment or therapy parameters intothe treatment or therapy device such that the treatment or therapydevice provides treatment or therapy to the subject based on thesuggested set of parameters.
 16. The system of claim 15, wherein thecorrelation algorithm is a machine learning algorithm.
 17. The system ofclaim 16, further comprising a movement disorder diagnostic devicecomprising at least one at least one movement sensor adapted to measurethe subject's movement disorder symptoms and/or side effects oftreatment or therapy of the subject's movement disorder during at leasta first and second time periods substantially simultaneously withmeasurement of brain activity, and the system also further comprises atleast one processor comprising at least one quantification algorithmadapted to calculate a quantification of severity of the subject'smovement disorder symptoms and/or side effects of treatment or therapyof the subject's movement disorder during each of the at least first andsecond time periods substantially simultaneously with the measurement ofthe subject's movement disorder symptoms and/or side effects oftreatment or therapy.
 18. The system of claim 16, wherein the brainactivity measurement component comprises at least one dual-mode deepbrain stimulation (DBS) lead with a plurality of contacts adapted toprovide electrical stimulation and to acquire physiological signals. 19.The system of claim 15, further comprising a display device adapted toreceive the measured brain activity as input and to display suchmeasured brain activity in the form of a 2D or 3D image of the subject'sbrain concurrently with a tuning map presenting the calculatedquantification of severity of symptoms and/or side effects associatedwith the measured brain activity being displayed.
 20. The system ofclaim 18, wherein the at least one dual-mode DBS lead is adapted tosimultaneously provide electrical stimulation from one or more of theplurality of contacts on the lead and acquire electrophysiologicalsignals from the subject from one or more of the plurality of contactson the lead.